CN106339428A - Identity identification method and device for suspects based on large video data - Google Patents
Identity identification method and device for suspects based on large video data Download PDFInfo
- Publication number
- CN106339428A CN106339428A CN201610677700.3A CN201610677700A CN106339428A CN 106339428 A CN106339428 A CN 106339428A CN 201610677700 A CN201610677700 A CN 201610677700A CN 106339428 A CN106339428 A CN 106339428A
- Authority
- CN
- China
- Prior art keywords
- suspect
- information
- moving target
- characteristic information
- video
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
- G06F16/7837—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using objects detected or recognised in the video content
- G06F16/784—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using objects detected or recognised in the video content the detected or recognised objects being people
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/20—Movements or behaviour, e.g. gesture recognition
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Library & Information Science (AREA)
- Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Health & Medical Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Health & Medical Sciences (AREA)
- Psychiatry (AREA)
- Social Psychology (AREA)
- Human Computer Interaction (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Image Analysis (AREA)
Abstract
The invention provides an identity identification method and device for suspects based on large video data. The identity identification method comprises the following steps: receiving suspect characteristic information transmitted by a user; carrying out cluster retrieval on a moving target which is matched with the suspect characteristic information from a moving target characteristic database, and extracting characteristic information which is corresponding to the moving target; obtaining base station data corresponding to the characteristic information within a motion range according to the extracted characteristic information; extracting suspect identity information matched with the moving target from an identity information platform device according to the base station data corresponding to the characteristic information within the motion range. The identity identification method is combined with multi-aspect resources of the moving target characteristic database, the base station data, resident population data in the identity information platform device and the like to carry out comprehensive collision retrieval, so that accurate video suspect identity information can be obtained to greatly improve the accuracy and success rate of the suspect identity information identification; furthermore, a large data analysis and processing technology is used, so that a large number of high-speed changeable complex scenes can be dealt, and the timeliness is better.
Description
Technical field
The present invention relates to technical field of video processing, in particular to a kind of suspicion based on video big data person
Part recognition methods and device.
Background technology
In recent years, with the reinforcement of ruling by law dynamics, each the important common point in China city has been respectively mounted monitoring
Camera, for obtaining the video data in its monitoring range in real time and being stored, in order to assist the detection case of public security organ
Part, to ensure the living safety of resident.In society now, the Main Means of public security organ's clear up a criminal case call place of committing a crime
The video monitoring information of surrounding, and find and position suspect's clue of Related Cases accordingly.And in above-mentioned clear up a criminal case process
In, positioning is identified to the identity information of the suspect in associated video and is particularly important.
At present, relatively advanced video suspect's identity information recognition methods relies on face recognition technology.Above-mentioned face
Technology of identification is that organism (typically the refering in particular to people) biological characteristic of itself is distinguished with organism individuality.Specifically, first determine whether
Whether there is face in corresponding monitor video, if there is face, then need to calculate position, size and the people of each face
The positional information of each major facial organ and characteristic information in face, then according to the above- mentioned information drawing, extract every further
The identity characteristic containing in individual face, it is right finally to carry out the identity characteristic of extraction and pre-stored face feature in Relational database
Ratio is thus identify the corresponding identity information of each face.
But, method for distinguishing can there are the following problems to carry out the knowledge of video suspect's identity information above by recognition of face:
First, due to the shooting angle problem of camera, the video data that video monitoring system collects may not include human face data
(or only comprising a part of human face data), thus video suspect's identity information cannot be carried out by above-mentioned face recognition technology
Identification.Second, the spot for photography of video monitoring system and video camera definition, exposure problem all can be to the faces collecting
The precision of data causes very big deviation.
Content of the invention
In view of this, the purpose of the embodiment of the present invention is to provide a kind of suspect's identification based on video big data
Method and apparatus, to improve the accuracy of identification of identity information.
In a first aspect, embodiments providing a kind of suspect's personal identification method based on video big data, institute
The method of stating includes:
Suspect's characteristic information that receive user sends；Described suspect's characteristic information at least includes the following letter of suspect
Breath: activity time scope, motion video point position information and figure and features characteristic information；
The moving target that Clustering Retrieval is matched with described suspect's characteristic information from moving target property data base, and
Extract described moving target corresponding space-time characteristic information；Described space-time characteristic information at least includes the following letter of moving target
Breath: activity time and video point position information；
According to the space-time characteristic information of the described moving target extracting, obtain described space-time characteristic information corresponding activity model
Base station data in enclosing；
According to the base station data in the corresponding scope of activities of described space-time characteristic information, carry from identity information stage apparatus
Take the suspect's identity information matching with described moving target.
In conjunction with a first aspect, embodiments providing the first possible embodiment of first aspect, wherein, institute
State the moving target that Clustering Retrieval is matched with described suspect's characteristic information from moving target property data base, and extract institute
State moving target corresponding space-time characteristic information, comprising:
Activity time scope according to suspect and motion video point position information, from described moving target property data base
Load the moving target characteristic information of coupling；
According to the figure and features characteristic information of suspect, search the motion of coupling from the described moving target characteristic information loading
Target, and determine that this moving target is suspect's target；
Extract the space-time characteristic information of described suspect's target.
In conjunction with the first possible embodiment of first aspect, embodiments provide the second of first aspect
Possible embodiment, wherein, the described space-time characteristic information according to the described moving target extracting, obtain described space-time characteristic
Base station data in the corresponding scope of activities of information, comprising:
According to the sequencing of suspect's activity time, the space-time characteristic information of the described suspect's target extracted is carried out
Sequence is processed, and obtains suspect's trace information sample；
According to the corresponding latitude and longitude information of suspect's motion video point position information, described suspect track is drawn on map
Information sample corresponding suspect event trace information；
According to described suspect's event trace information, obtain in the corresponding scope of activities of described suspect's event trace information
All base sites positions information.
In conjunction with the possible embodiment of the second of first aspect, embodiments provide first aspect the third
Possible embodiment, wherein, base station data in the described corresponding scope of activities according to described space-time characteristic information, from identity
The suspect's identity information matching with described moving target is extracted in information platform device, comprising:
In the range of the activity time of described suspect, obtain the movement accessing in each described base sites position information and set
Standby；
From all mobile devices obtaining, search the mobile device accessing all base sites positions information and described movement
Equipment accesses the turn-on time of each base sites position information；
The mobile device with described suspect's event trace information match is filtered out from lookup result；
According to the identification information of described mobile device, mobile device operator platform is searched described mobile device and corresponds to
Authentication information；
According to described authentication information, public security big data platform is searched suspect's identity information of coupling.
In conjunction with the third possible embodiment of first aspect, embodiments provide the 4th kind of first aspect
Possible embodiment, wherein, described moving target property data base is to set up previously according to following methods:
Receive the video data that image acquisition device sends；
Extract the characteristic information of moving target in each frame video image and described moving target respectively；
The characteristic information of described moving target and described moving target is stored in database, obtains described motion mesh
Mark property data base.
In conjunction with the 4th kind of possible embodiment of first aspect, embodiments provide the 5th kind of first aspect
Possible embodiment, wherein, the described characteristic information by described moving target and described moving target is stored in database
In, comprising:
According to the characteristic information of described moving target, generate the feature tag corresponding to moving target each described；Institute
State feature tag at least to include: activity time label, video point position information labels and figure and features characteristic information label；
Each feature tag generating is added in corresponding described moving target；
All moving targets carrying described feature tag are stored in database.
Second aspect, the embodiment of the present invention additionally provides a kind of suspect's identity recognition device based on video big data,
Described device includes:
First receiver module, the suspect's characteristic information sending for receive user；Described suspect's characteristic information is at least
Following information including suspect: activity time scope, motion video point position information and figure and features characteristic information；
Clustering Retrieval module, for Clustering Retrieval from moving target property data base and described suspect's characteristic information phase
The moving target of coupling, and extract described moving target corresponding space-time characteristic information；Described space-time characteristic information at least includes
The following information of moving target: activity time and video point position information；
Acquisition module, for the space-time characteristic information according to the described moving target extracting, obtains described space-time characteristic letter
Cease the base station data in corresponding scope of activities；
First extraction module, for according to the base station data in the corresponding scope of activities of described space-time characteristic information, from body
Extract, in part information platform device, the suspect's identity information matching with described moving target.
In conjunction with second aspect, embodiments provide the first possible embodiment of second aspect, wherein, institute
State Clustering Retrieval module, comprising:
Loading unit, for the activity time scope according to suspect and motion video point position information, from described motion mesh
The moving target characteristic information of coupling is loaded in mark property data base；
Searching unit, for the figure and features characteristic information according to suspect, from the described moving target characteristic information loading
Search the moving target of coupling, and determine that this moving target is suspect's target；
Extraction unit, for extracting the space-time characteristic information of described suspect's target.
In conjunction with the first possible embodiment of second aspect, embodiments provide the second of second aspect
Possible embodiment, wherein, described acquisition module, comprising:
Sequencing unit, for the sequencing according to suspect's activity time, to the described suspect's target extracted when
Empty characteristic information is ranked up processing, and obtains suspect's trace information sample；
Drawing unit, for according to the corresponding latitude and longitude information of suspect's motion video point position information, drawing on map
The corresponding suspect's event trace information of described suspect's trace information sample；
First acquisition unit, for according to described suspect's event trace information, obtaining described suspect's event trace letter
Cease all base sites positions information in corresponding scope of activities.
In conjunction with the possible embodiment of the second of second aspect, embodiments provide second aspect the third
Possible embodiment, wherein, described first extraction module, comprising:
Second acquisition unit, in the range of the activity time of described suspect, obtaining each described base sites position
The mobile device accessing in information；
First searching unit, for, from all mobile devices obtaining, searching the shifting accessing all base sites positions information
Dynamic equipment and described mobile device access the turn-on time of each base sites position information；
Screening subelement, for filtering out the movement with described suspect's event trace information match from lookup result
Equipment；
Second searching unit, for the identification information according to described mobile device, looks in mobile device operator platform
Look for the corresponding authentication information of described mobile device；
3rd searching unit, for according to described authentication information, searching the suspicion of coupling in public security big data platform
Doubtful people's identity information.
In conjunction with the third possible embodiment of second aspect, embodiments provide the 4th kind of second aspect
Possible embodiment, wherein, above-mentioned suspect's identity recognition device based on video big data, also include:
Second receiver module, for receiving the video data of image acquisition device transmission；
Second extraction module, for extracting the spy of the moving target in each frame video image and described moving target respectively
Reference ceases；
Memory module, for the characteristic information of described moving target and described moving target is stored in database,
Obtain described moving target property data base.
In conjunction with the 4th kind of possible embodiment of second aspect, embodiments provide the 5th kind of second aspect
Possible embodiment, wherein, described memory module, comprising:
Signal generating unit, for the characteristic information according to described moving target, generates corresponding to moving target each described
Feature tag；Described feature tag at least includes: activity time label, video point position information labels and figure and features characteristic information mark
Sign；
Adding device, for being added to each feature tag generating in corresponding described moving target；
Memory cell, for all moving targets carrying described feature tag are stored in database.
A kind of suspect's personal identification method based on video big data provided in an embodiment of the present invention and device, comprising:
Suspect's characteristic information that receive user sends；Clustering Retrieval and suspect's characteristic information phase from moving target property data base
The moving target of coupling, and extract the corresponding characteristic information of moving target；According to the characteristic information extracting, obtain characteristic information pair
The base station data in scope of activities answered；According to the base station data in the corresponding scope of activities of characteristic information, put down from identity information
The suspect's identity information matching with moving target is extracted in table apparatus；
Compared with undesirable with the video suspect's identity information identification being carried out by recognition of face mode in prior art, its
In conjunction with the many-side resource such as resident demographic data in moving target property data base, base station data and identity information stage apparatus
Carry out comprehensively colliding retrieval, the accurate information of video suspect's identity can be obtained, substantially increase suspect's identity information and know
Other accuracy rate and success rate；And, technology is analyzed and processed using big data, a large amount of, complicated field at a high speed, changeable can be processed
Scape, ageing preferable.
Further, a kind of suspect's personal identification method based on video big data provided in an embodiment of the present invention and dress
Put, its analysis result generalization, not only can provide video suspect's identity accurate information moreover it is possible to comprehensive provide suspect to commit a crime
Motion track information in front and back, cellphone information, the figure painting that permanent information, trip information etc. complete, as information, is more beneficial for the people
Police handles a case.
For enabling the above objects, features and advantages of the present invention to become apparent, preferred embodiment cited below particularly, and coordinate
Appended accompanying drawing, is described in detail below.
Brief description
In order to be illustrated more clearly that the technical scheme of the embodiment of the present invention, below will be attached to use required in embodiment
Figure is briefly described it will be appreciated that the following drawings illustrate only certain embodiments of the present invention, and it is right to be therefore not construed as
The restriction of scope, for those of ordinary skill in the art, on the premise of not paying creative work, can also be according to this
A little accompanying drawings obtain other related accompanying drawings.
Fig. 1 shows a kind of suspect's personal identification method based on video big data that the embodiment of the present invention is provided
Flow chart；
Fig. 2 shows that one kind that the embodiment of the present invention is provided utilizes big data retrieval technique, from moving target characteristic
The moving target matching with described suspect's characteristic information according to Clustering Retrieval in storehouse, and extract described moving target corresponding when
The flow chart of empty characteristic information；
Fig. 3 shows a kind of space-time characteristic letter according to the described moving target extracting that the embodiment of the present invention is provided
Breath, the flow chart obtaining the base station data in the corresponding scope of activities of described space-time characteristic information；
Fig. 4 shows one kind that the embodiment of the present invention provided according in the corresponding scope of activities of described space-time characteristic information
Base station data, extract the flow process of suspect's identity information matching with described moving target from identity information stage apparatus
Figure；
Fig. 5 shows that a kind of video data according to image acquisition device collection that the embodiment of the present invention is provided sets up motion
The flow chart of target characteristic database；
Fig. 6 shows a kind of suspect's identity recognition device based on video big data that the embodiment of the present invention is provided
Structural representation；
Fig. 7 show that the embodiment of the present invention provided a kind of based in suspect's identity recognition device of video big data
Clustering Retrieval module and the structural representation of acquisition module；
Fig. 8 show that the embodiment of the present invention provided a kind of based in suspect's identity recognition device of video big data
First extraction module and the structural representation of memory module；
Fig. 9 shows another kind that the embodiment of the present invention the provided suspect's identity recognition device based on video big data
Structural representation.
Major Symbol illustrates:
10th, the first receiver module；20th, Clustering Retrieval module；30th, acquisition module；40th, the first extraction module；50th, second connect
Receive module；60th, the second extraction module；70th, memory module；201st, loading unit；202nd, the first searching unit；203rd, extract list
Unit；301st, sequencing unit；302nd, drawing unit；303rd, first acquisition unit；401st, second acquisition unit；402nd, second search list
Unit；403rd, screen subelement；404th, the 3rd searching unit；405th, the 4th searching unit；701st, signal generating unit；702nd, add list
Unit；703rd, memory cell.
Specific embodiment
Purpose, technical scheme and advantage for making the embodiment of the present invention are clearer, below in conjunction with the embodiment of the present invention
Middle accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described it is clear that described embodiment only
It is a part of embodiment of the present invention, rather than whole embodiments.The present invention generally described and illustrated in accompanying drawing herein is real
The assembly applying example can be arranged with various different configurations and design.Therefore, below to the present invention's providing in the accompanying drawings
The detailed description of embodiment is not intended to limit the scope of claimed invention, but is merely representative of the selected reality of the present invention
Apply example.Based on embodiments of the invention, the institute that those skilled in the art are obtained on the premise of not making creative work
There is other embodiment, broadly fall into the scope of protection of the invention.
In society now, the Main Means that public security is solved a case are to be believed by checking the video monitoring around place of committing a crime
Breath, finds positioning Related Cases suspect's clue.But, a problem of current generally existing is people's police according to suspect's video
The true identity of suspect occurring in image analysing computer video and its event trace, needs take considerable time, man power and material,
Complicated show the true identity that the means of surveying finally position suspect in conjunction with various.
Consider be all up till now by recognition of face carry out video suspect's identity information know method for distinguishing can exist as follows
Problem: first, due to the shooting angle problem of camera, the video data that video monitoring system collects may not include face
Data (or only comprising a part of human face data), thus video suspect's identity cannot be carried out by above-mentioned face recognition technology
Information identifies.Second, the spot for photography of video monitoring system and video camera definition, exposure problem all can be to collecting
The precision of human face data causes very big deviation；3rd, because recognition of face is the facial image and public affairs arriving video acquisition
Pacify local suspect storehouse face picture to compare, and public security local face database data is limited, causes lower than middle possibility.Logical
Cross this means and finally cannot determine suspect's identity information.Based on this, embodiments provide a kind of big based on video
Suspect's personal identification method of data and device, are described below by embodiment.
Embodiments provide a kind of suspect's personal identification method based on video big data, methods described is based on
Big data platform executes, and with reference to Fig. 1, methods described specifically includes following steps:
Suspect's characteristic information that s101, receive user send；Described suspect's characteristic information at least includes suspect's
Following information: activity time scope, motion video point position information and figure and features characteristic information.
Method provided in an embodiment of the present invention is mainly handled a case use for people's police；First, received by big data platform and do
The characteristic information of the suspect that commits a crime of case people's police input, features described above information at least includes: the figure and features feature of suspect, such as body
High, profile (such as: long hair, bob, have scar etc. on the face) and clothing etc., the activity time scope of suspect, that is, need retrieval
Time；And, motion video point position information, that is, need the video point position information retrieved.
S102, the motion mesh that Clustering Retrieval is matched with described suspect's characteristic information from moving target property data base
Mark, and extract above-mentioned moving target corresponding space-time characteristic information；Above-mentioned space-time characteristic information at least include moving target with
Lower information: activity time and video point position information.
Specifically, it is previously stored with the structurized video data of magnanimity in above-mentioned moving target property data base, above-mentioned regard
Frequency evidence is front-end image collector, and big data platform carries out structuring process to the moving target in above-mentioned video data
Afterwards, it is stored in processing the moving target obtaining in moving target property data base, wherein, above-mentioned moving target is multiple to having
Label, such as time of occurrence, video point position information (numbering of the image acquisition device being located, described numbering to should have collecting location)
Figure and features feature (as height and five official ranks of people) with moving target.
Then, suspect's characteristic information is inputted in big data platform according to policeman in charge of the case, big data platform is then according to upper
State suspect's characteristic information, the fortune that Clustering Retrieval is matched in its moving target property data base with this suspect's characteristic information
Moving-target, meanwhile, extracts above-mentioned moving target corresponding space-time characteristic information, comprising: activity time and video point position information.
S103, the space-time characteristic information according to the described moving target extracting, obtain described space-time characteristic information corresponding
Base station data in scope of activities.
In this step, big data platform can be drawn according to the activity time of the suspect extracting and video point position information and dislike
The event trace of doubtful people, then extracts the mobile device base station data of the event trace periphery of suspect；Wherein, above-mentioned suspect
The scope of event trace periphery can be configured in advance.
S104, according to the base station data in the corresponding scope of activities of described space-time characteristic information, from identity information platform dress
Put the middle suspect's identity information extracting and matching with described moving target.
In this step, big data platform, according to all base station datas obtaining, is positioned at the activity time scope of suspect
Interior, access the mobile device of above-mentioned all base stations, then, according to the above-mentioned mobile device of positioning, connect in advance in big data platform
The suspect's identity information matching with the moving target extracting is extracted in the identity information stage apparatus entering.Wherein, above-mentioned body
Part information platform device can be mobile device operator platform and public security big data platform；Can also be to access above-mentioned movement to set
Standby operator's platform and the third-party platform of public security big data platform.
Wherein, the corresponding phone number of network of its operation, above-mentioned mobile phone are stored in above-mentioned mobile device operator platform
The numbering of the base station that number accesses in Preset Time and, the mobile device sequence number of above-mentioned phone number association and user's
ID card information；Big data platform then passes through all base station datas obtaining, and from above-mentioned mobile device operator platform, obtains
The ID card information of suspect.
It is previously stored with, in above-mentioned public security big data platform, the essential information data that mobile device holds each user；On
State the database being divided into multiple classifications in the database of public security big data platform in advance, such as population essential information storehouse, fugitive people
Member storehouse, personnel concerning the case storehouse, trip record storehouse, hotel hotel storehouse etc., and, it is corresponding to be all stored with each database above-mentioned
Personal information.
The big data platform then ID card information according to the suspect obtaining, in the database of above-mentioned public security big data platform
In collision carried out to the ID card information of above-mentioned suspect compare, with the full identity information of the case-involving suspect of positioning video: bag
Include the identification card number of suspect, name, home address, permanent address, whether be previous conviction personnel, whether be fugitive personnel, commit a crime
Have in front and back which trip record (such as sitting which train, aircraft and automobile etc.), firmly which hotel, hotel, finally, according to upper
The full identity information stating suspect draws the complete figure painting picture of suspect, so that policeman in charge of the case can be violated with fast track
Case suspect.
In above-mentioned steps 101～step 104, all comparisons, analytical technology are all transported automatically using backstage big data cluster environment
Complete.Wherein, the process carrying out above-mentioned computing adopts distributed treatment, concurrent operation mass data, and comparison result second level is returned
Return, suspect's identity result can be pushed to policeman in charge of the case within the extremely short time, efficiency of accelerating to solve a case.
A kind of suspect's personal identification method based on video big data provided in an embodiment of the present invention, in prior art
Carried out by recognition of face mode video suspect's identity information identification undesirable compare, its combine moving target characteristic
The many-side resource such as resident demographic data in storehouse, base station data and identity information stage apparatus carries out comprehensively colliding retrieval, energy
Access the accurate information of video suspect's identity, substantially increase accuracy rate and the success rate of the identification of suspect's identity information；
And, technology is analyzed and processed using big data, a large amount of, complex scene at a high speed, changeable can be processed, ageing preferable.
Further, with reference to Fig. 2, above-mentioned steps 102 are using big data retrieval technique, from moving target property data base
The moving target that middle Clustering Retrieval is matched with described suspect's characteristic information, and it is special to extract the corresponding space-time of described moving target
Reference ceases, and specifically includes following steps:
S201, the activity time scope according to suspect and motion video point position information, from described moving target characteristic
According to the moving target characteristic information loading coupling in storehouse.
Big data retrieval technique in the embodiment of the present invention is using spark and hdfs distributed file system；Wherein, on
State the universal parallel framework that spark is the class hadoop mapreduce that uc berkeley amp lab is increased income.
Specifically, big data platform utilize above-mentioned big data retrieval technique, according to people's police input suspect movable when
Between scope and suspect motion video point position information search condition, from moving target property data base screening meet above-mentioned inspection
The video structural data of rope condition, and above-mentioned video structural data is loaded in spark distributed elastic internal memory.
S202, the figure and features characteristic information according to suspect, search coupling from the described moving target characteristic information loading
Moving target, and determine this moving target be suspect's target.
Specifically, the figure and features characteristic information of the suspect according to people's police's input and the moving target of loading in step 201
Figure and features feature tag is contrasted, and the description if there is the figure and features feature tag of moving target meets the retrieval bar that people's police input
Part is it is determined that corresponding moving target is suspect's target.
S203, the space-time characteristic information of the described suspect's target of extraction.
Specifically, in the suspect's characteristic information being inputted according to people's police, after located suspect's target, from above-mentioned motion mesh
Video point position and the time of occurrence that above-mentioned suspect's target occurs is extracted in mark property data base.
Further, with reference to Fig. 3, in above-mentioned steps 103, according to the space-time characteristic information of the described moving target extracting,
Obtain the base station data in the corresponding scope of activities of described space-time characteristic information, comprising:
S301, according to suspect's activity time sequencing, to extract described suspect's clarification of objective information enter
Row sequence is processed, and obtains suspect's trace information sample.
Specifically, all results that meet of the space-time characteristic information of the suspect's target extracted in step 202 are converged
Always, simultaneously according to the sequencing of suspect's activity time, above-mentioned space-time characteristic information is resequenced, generate suspect
Trace information sample, such as suspect's activity time can be 1:00,2:00 and 3:00；Corresponding, the image acquisition device at place
Point position information is a point position, b point position and c point position；Therefore the suspect's trace information sample after sequence is as follows: 1:00 (a point position) >
2:00 (b point position) > 3:00 (c point position).
S302, according to the corresponding latitude and longitude information of suspect's motion video point position information, described suspicion is drawn on map
People's trace information sample corresponding suspect event trace information.
Specifically, the image acquisition device of each numbering, all to there being its default pickup area, obtains suspect's activity and regards
The corresponding latitude and longitude information of frequency position information, then according to this latitude and longitude information in pgis (police geographic
Information system, Police Geographic Information System) portray the complete space-time trace information of this suspect in map and (i.e. should
The event trace information based on time and space for the suspect).
S303, according to described suspect's event trace information, obtain the corresponding activity of described suspect's event trace information
In the range of all base sites positions information.
Specifically, the latitude and longitude information first according to suspect's complete active scope searches all base sites positions in the range of this
Then information, when pulling suspect according to specific base sites bit number and occurring from the base station information storehouse of public security big data platform
Between before and after all mobile devices (including the mobile device of suspect in this all mobile device) connect base station concrete letter
Breath.
Further, with reference to Fig. 4, above-mentioned based in suspect's personal identification method of video big data, step 104, root
According to the base station data in the corresponding scope of activities of described space-time characteristic information, extract and described fortune from identity information stage apparatus
Suspect's identity information that moving-target matches, comprising:
S401, in the range of the activity time of described suspect, obtain in each described base sites position information access
Mobile device.
S402, from all mobile devices obtaining, search the mobile device accessing all base sites positions information and institute
State the turn-on time that mobile device accesses each base sites position information.
S403, filter out mobile device with described suspect's event trace information match from lookup result.
S404, the identification information according to described mobile device, search described movement in mobile device operator platform and set
Standby corresponding authentication information.
Wherein, the identification information of above-mentioned mobile device is the sequence number of mobile device, and above-mentioned authentication information can be
The ID card information of suspect, i.e. ID card No.；Specifically, the sequence number according to above-mentioned mobile device can be from mobile device
This corresponding phone number of this mobile device is found, then the mobile device of the suspect by finding in operator's platform
Phone number would know that the ID card No. of suspect.
S405, according to described authentication information, public security big data platform is searched suspect's identity information of coupling.
In conjunction with above-mentioned steps 401 to step 405, this model is being searched according to the latitude and longitude information of suspect's complete active scope
After enclosing interior all base sites positions information, first according to specific base sites bit number from identity information stage apparatus (as public security is big
Data platform) in base station information storehouse in pull before and after suspect's time of occurrence all mobile devices (this all of movement sets
The standby mobile device including suspect) connect the specifying information of base station, this specifying information include mobile device sequence number and
The information such as the numbering of base station of this mobile device access, time；
Then, according to the above-mentioned specifying information obtaining, to the above-mentioned base station movement device data information collecting using big
Data collision analytical technology, finds out the phone number of suspect.Specific implementation includes:
1st, the base station data extracting is loaded in spark elasticity internal memory processed.
2nd, pass through spark clustering technique, using cell-phone number as statistical dimension, count each mobile device (as mobile phone sets
Standby) occurred in which base sites position.
3rd, statistics in 2 is screened further, filter out the mobile device occurring in all base sites positions, such as mobile phone sets
Time that standby sequence number, cell phone apparatus occur etc..
4th, the result filtering out in 3 and suspect's event trace time are contrasted, finally filter out and meet suspect
The cell phone apparatus of event trace, then directly or indirectly obtain from mobile device operator platform according to the cell phone apparatus filtering out
The authentication information getting the corresponding phone number of this mobile device and the corresponding suspect of this phone number is (as identity card
Number)；
5th, last, according to the identification card number of suspect, public security big data platform is searched suspect's identity letter of coupling
Breath.
In addition, carry out suspect's identity information in prior art to know method for distinguishing is all the direct number from surveillance video
" the video point position information " occurring according to middle positioning suspect, the program is complicated and wastes time and energy.In the embodiment of the present invention, right first
The monitor video data of image acquisition device collection carries out structuring process, and the result that structuring process is obtained stores motion
In target characteristic database, then entered in moving target property data base according to suspect's characteristic information of policeman in charge of the case's input
Line retrieval.Specifically, it is that moving target characteristic is set up according to the video data of image acquisition device collection in the embodiment of the present invention
According to storehouse, with reference to Fig. 5, concrete method for building up is as follows:
The video data that s501, reception image acquisition device send.
Specifically, first with tcp/udp agreement, the image acquisition device of front end is accessed big data platform, image acquisition device
Then the monitor video collecting data is sent to big data platform in the way of video flowing.
S502, extract the space-time characteristic information of moving target in each frame video image and described moving target respectively.
Specifically, in units of frame of video, in analysis video flowing, all motion mesh to big data platform in each two field picture
Mark, and the corresponding characteristic information of each moving target (as activity time, video point position information and figure and features characteristic information).
S503, the space-time characteristic information of described moving target and described moving target is stored in database, obtains
Described moving target property data base.
Specifically, the space-time characteristic information of the above-mentioned moving target being obtained according to analysis, generates corresponding to described in each
The feature tag of moving target；Described feature tag at least includes: activity time label, video point position information labels and figure and features are special
Levy information labels；Then, each feature tag generating is added in corresponding described moving target；Carry all
The moving target having described feature tag is stored in database.Wherein, figure and features characteristic information label can also include multiple
Subtab, such as build, the colour of skin, clothing, local feature etc., wherein, label setting more many more become the retrieval more subsequently carrying out.This
In inventive embodiments, with the activity time scope of moving target+motion video point position information (i.e. space time information) position as key, with
Other features (as figure and features characteristic information) of moving target are value, and above-mentioned moving target and corresponding label are stored
In hdfs distributed file system.Follow-up, according to suspect's characteristic information of user input, in moving target property data base
Middle Clustering Retrieval to coupling moving target after, then return this moving target key (moving target occur video point position with
And time of occurrence), i.e. the characteristic information of suspect.
A kind of suspect's personal identification method based on video big data provided in an embodiment of the present invention, in prior art
Carried out by recognition of face mode video suspect's identity information identification undesirable compare, its combine moving target characteristic
The many-side resource such as resident demographic data in storehouse, base station data and identity information stage apparatus carries out comprehensively colliding retrieval, energy
Access the accurate information of video suspect's identity, substantially increase accuracy rate and the success rate of the identification of suspect's identity information；
And, technology is analyzed and processed using big data, a large amount of, complex scene at a high speed, changeable can be processed, ageing preferable.
Further, a kind of suspect's personal identification method based on video big data provided in an embodiment of the present invention, its
Analysis result generalization, before and after not only can providing video suspect's identity accurate information moreover it is possible to comprehensively provide suspect to commit a crime
Motion track information, cellphone information, the figure painting that permanent information, trip information etc. complete, as information, is more beneficial for people's police and does
Case.
The embodiment of the present invention additionally provides a kind of suspect's identity recognition device based on video big data, and described device is used
In executing above-mentioned suspect's personal identification method based on video big data, with reference to Fig. 6, described device is big data platform, its
Specifically include:
First receiver module 10, the suspect's characteristic information sending for receive user；Suspect's characteristic information at least wraps
Include the following information of suspect: activity time scope, motion video point position information and figure and features characteristic information；
Clustering Retrieval module 20, for Clustering Retrieval from moving target property data base and described suspect's characteristic information
The moving target matching, and extract described moving target corresponding space-time characteristic information；Described space-time characteristic information is at least wrapped
Include the following information of moving target: activity time and video point position information；
Acquisition module 30, for the space-time characteristic information according to the described moving target extracting, obtains described space-time characteristic
Base station data in the corresponding scope of activities of information；
First extraction module 40, for according to the base station data in the corresponding scope of activities of described space-time characteristic information, from
The suspect's identity information matching with described moving target is extracted in identity information stage apparatus.
Further, with reference to Fig. 7, above-mentioned based in suspect's identity recognition device of video big data, Clustering Retrieval module
20, comprising:
Loading unit 201, for the activity time scope according to suspect and motion video point position information, from moving target
The moving target characteristic information of coupling is loaded in property data base；
First searching unit 202, for the figure and features characteristic information according to suspect, from the moving target characteristic information loading
The middle moving target searching coupling, and determine that this moving target is suspect's target；
Extraction unit 203, for extracting the space-time characteristic information of described suspect's target.
Further, with reference to Fig. 7, above-mentioned based in suspect's identity recognition device of video big data, acquisition module 30, bag
Include:
Sequencing unit 301, for the sequencing according to suspect's activity time, to the described suspect's target extracted
Space-time characteristic information is ranked up processing, and obtains suspect's trace information sample；
Drawing unit 302, for according to the corresponding latitude and longitude information of suspect's motion video point position information, painting on map
Make the corresponding suspect's event trace information of described suspect's trace information sample；
First acquisition unit 303, for according to described suspect's event trace information, obtaining described suspect's event trace
All base sites positions information in the corresponding scope of activities of information.
Further, with reference to Fig. 8, above-mentioned based in suspect's identity recognition device of video big data, the first extraction module
40, comprising:
Second acquisition unit 401, in the range of the activity time of suspect, obtaining in each base sites position information
The mobile device accessing；
Second searching unit 402, for, from all mobile devices obtaining, searching and accessing all base sites positions information
Mobile device and mobile device access the turn-on time of each base sites position information；
Screening subelement 403, for filtering out the movement with suspect's event trace information match from lookup result
Equipment；
3rd searching unit 404, for the identification information according to mobile device, searches in mobile device operator platform
The corresponding authentication information of mobile device；
4th searching unit 405, for according to described authentication information, searching coupling in public security big data platform
Suspect's identity information.
Further, with reference to Fig. 9, above-mentioned also included based on suspect's identity recognition device of video big data:
Second receiver module 50, for receiving the video data of image acquisition device transmission；
Second extraction module 60, for extracting the space-time of the moving target in each frame video image and moving target respectively
Characteristic information；
Memory module 70, for being stored in the space-time characteristic information of moving target and moving target in database, obtains
To moving target property data base.
Further, with reference to Fig. 8, above-mentioned based in suspect's identity recognition device of video big data, memory module 70, bag
Include:
Signal generating unit 701, for the space-time characteristic information according to moving target, generates corresponding to each moving target
Feature tag；Feature tag at least includes: activity time label, video point position information labels and figure and features characteristic information label；
Adding device 702, for being added to each feature tag generating in corresponding moving target；
Memory cell 703, for all moving targets carrying feature tag are stored in database.
A kind of suspect's identity recognition device based on video big data provided in an embodiment of the present invention, in prior art
Carried out by recognition of face mode video suspect's identity information identification undesirable compare, its combine moving target characteristic
The many-side resource such as resident demographic data in storehouse, base station data and identity information stage apparatus carries out comprehensively colliding retrieval, energy
Access the accurate information of video suspect's identity, substantially increase accuracy rate and the success rate of the identification of suspect's identity information；
And, technology is analyzed and processed using big data, a large amount of, complex scene at a high speed, changeable can be processed, ageing preferable.
Further, a kind of suspect's identity recognition device based on video big data provided in an embodiment of the present invention, its
Analysis result generalization, before and after not only can providing video suspect's identity accurate information moreover it is possible to comprehensively provide suspect to commit a crime
Motion track information, cellphone information, the figure painting that permanent information, trip information etc. complete, as information, is more beneficial for people's police and does
Case.
The device of the suspect's identification based on video big data that the embodiment of the present invention is provided can be on equipment
Specific hardware or be installed on software or firmware on equipment etc..The device that the embodiment of the present invention is provided, it realizes principle
And the technique effect of generation is identical with preceding method embodiment, for briefly describing, device embodiment part does not refer to part, can join
State corresponding contents in embodiment of the method before examination.Those skilled in the art can be understood that, for description convenience and
Succinctly, the specific work process of system described above, device and unit, all may be referred to the correspondence in said method embodiment
Process, will not be described here.
It should be understood that disclosed apparatus and method in embodiment provided by the present invention, other sides can be passed through
Formula is realized.Device embodiment described above is only that schematically for example, the division of described unit, only one kind are patrolled
Volume function divides, and actual can have other dividing mode when realizing, and for example, multiple units or assembly can in conjunction with or can
To be integrated into another system, or some features can be ignored, or does not execute.Another, shown or discussed each other
Coupling or direct-coupling or communication connection can be by some communication interfaces, the INDIRECT COUPLING of device or unit or communication link
Connect, can be electrical, mechanical or other forms.
The described unit illustrating as separating component can be or may not be physically separate, show as unit
The part showing can be or may not be physical location, you can with positioned at a place, or can also be distributed to multiple
On NE.The mesh to realize this embodiment scheme for some or all of unit therein can be selected according to the actual needs
's.
In addition, each functional unit in the embodiment that the present invention provides can be integrated in a processing unit, also may be used
To be that unit is individually physically present it is also possible to two or more units are integrated in a unit.
If described function realized using in the form of SFU software functional unit and as independent production marketing or use when, permissible
It is stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially in other words
Partly being embodied in the form of software product of part that prior art is contributed or this technical scheme, this meter
Calculation machine software product is stored in a storage medium, including some instructions with so that a computer equipment (can be individual
People's computer, server, or network equipment etc.) execution each embodiment methods described of the present invention all or part of step.
And aforesaid storage medium includes: u disk, portable hard drive, read-only storage (rom, read-only memory), arbitrary access are deposited
Reservoir (ram, random access memory), magnetic disc or CD etc. are various can be with the medium of store program codes.
It should also be noted that similar label and letter expression similar terms in following accompanying drawing, therefore, once a certain Xiang Yi
It is defined in individual accompanying drawing, then do not need it to be defined further and explains in subsequent accompanying drawing, additionally, term " the
One ", " second ", " the 3rd " etc. are only used for distinguishing description, and it is not intended that indicating or hint relative importance.
Last it is noted that the specific embodiment of embodiment described above, the only present invention, in order to the present invention to be described
Technical scheme, be not intended to limit, protection scope of the present invention is not limited thereto, although with reference to the foregoing embodiments to this
Bright be described in detail, it will be understood by those within the art that: any those familiar with the art
The invention discloses technical scope in, it still can be modified to the technical scheme described in previous embodiment or can be light
It is readily conceivable that change, or equivalent is carried out to wherein some technical characteristics；And these modifications, change or replacement, do not make
The essence of appropriate technical solution departs from the spirit and scope of embodiment of the present invention technical scheme.The protection in the present invention all should be covered
Within the scope of.Therefore, protection scope of the present invention should be defined by described scope of the claims.
Claims (12)
1. a kind of suspect's personal identification method based on video big data is it is characterised in that methods described includes:
Suspect's characteristic information that receive user sends；Described suspect's characteristic information at least includes the following information of suspect:
Activity time scope, motion video point position information and figure and features characteristic information；
The moving target that Clustering Retrieval is matched with described suspect's characteristic information from moving target property data base, and extract
The corresponding space-time characteristic information of described moving target；Described space-time characteristic information at least includes the following information of moving target: lives
Dynamic time and video point position information；
According to the space-time characteristic information of the described moving target extracting, obtain in the corresponding scope of activities of described space-time characteristic information
Base station data；
According to the base station data in the corresponding scope of activities of described space-time characteristic information, from identity information stage apparatus extract with
Suspect's identity information that described moving target matches.
2. the suspect's personal identification method based on video big data according to claim 1 it is characterised in that described from
The moving target that in moving target property data base, Clustering Retrieval is matched with described suspect's characteristic information, and extract described fortune
Moving-target corresponding space-time characteristic information, comprising:
Activity time scope according to suspect and motion video point position information, load from described moving target property data base
The moving target characteristic information of coupling；
According to the figure and features characteristic information of suspect, search the motion mesh of coupling from the described moving target characteristic information loading
Mark, and determine that this moving target is suspect's target；
Extract the space-time characteristic information of described suspect's target.
3. the suspect's personal identification method based on video big data according to claim 2 is it is characterised in that described
According to the space-time characteristic information of the described moving target extracting, obtain the base station in the corresponding scope of activities of described space-time characteristic information
Data, comprising:
According to the sequencing of suspect's activity time, the space-time characteristic information of the described suspect's target extracted is ranked up
Process, obtain suspect's trace information sample；
According to the corresponding latitude and longitude information of suspect's motion video point position information, described suspect's trace information is drawn on map
Sample corresponding suspect event trace information；
According to described suspect's event trace information, obtain the institute in the corresponding scope of activities of described suspect's event trace information
There is base sites position information.
4. the suspect's personal identification method based on video big data according to claim 3 is it is characterised in that described
According to the base station data in the corresponding scope of activities of described space-time characteristic information, extract and described fortune from identity information stage apparatus
Suspect's identity information that moving-target matches, comprising:
In the range of the activity time of described suspect, obtain the mobile device accessing in each described base sites position information；
From all mobile devices obtaining, search the mobile device accessing all base sites positions information and described mobile device
Access the turn-on time of each base sites position information；
The mobile device with described suspect's event trace information match is filtered out from lookup result；
According to the identification information of described mobile device, mobile device operator platform is searched the corresponding body of described mobile device
Part authentication information；
According to described authentication information, public security big data platform is searched suspect's identity information of coupling.
5. the suspect's personal identification method based on video big data according to claim 4 is it is characterised in that described fortune
Moving-target property data base is to set up previously according to following methods:
Receive the video data that image acquisition device sends；
Extract the characteristic information of moving target in each frame video image and described moving target respectively；
The characteristic information of described moving target and described moving target is stored in database, obtains described moving target special
Levy database.
6. the suspect's personal identification method based on video big data according to claim 5 will be it is characterised in that described will
The characteristic information of described moving target and described moving target is stored in database, comprising:
According to the characteristic information of described moving target, generate the feature tag corresponding to moving target each described；Described spy
Levy label at least to include: activity time label, video point position information labels and figure and features characteristic information label；
Each feature tag generating is added in corresponding described moving target；
All moving targets carrying described feature tag are stored in database.
7. a kind of suspect's identity recognition device based on video big data is it is characterised in that described device includes:
First receiver module, the suspect's characteristic information sending for receive user；Described suspect's characteristic information at least includes
The following information of suspect: activity time scope, motion video point position information and figure and features characteristic information；
Clustering Retrieval module, is matched with described suspect's characteristic information for Clustering Retrieval from moving target property data base
Moving target, and extract described moving target corresponding space-time characteristic information；Described space-time characteristic information at least includes moving
The following information of target: activity time and video point position information；
Acquisition module, for the space-time characteristic information according to the described moving target extracting, obtains described space-time characteristic information pair
The base station data in scope of activities answered；
First extraction module, for according to the base station data in the corresponding scope of activities of described space-time characteristic information, from identity letter
Extract, in breath stage apparatus, the suspect's identity information matching with described moving target.
8. the suspect's identity recognition device based on video big data according to claim 7 is it is characterised in that described gather
Class retrieves module, comprising:
Loading unit, for the activity time scope according to suspect and motion video point position information, special from described moving target
Levy the moving target characteristic information loading coupling in database；
First searching unit, for the figure and features characteristic information according to suspect, from the described moving target characteristic information loading
Search the moving target of coupling, and determine that this moving target is suspect's target；
Extraction unit, for extracting the space-time characteristic information of described suspect's target.
9. the suspect's identity recognition device based on video big data according to claim 8 is it is characterised in that described obtain
Delivery block, comprising:
Sequencing unit, for the sequencing according to suspect's activity time, special to the space-time of the described suspect's target extracted
Reference breath is ranked up processing, and obtains suspect's trace information sample；
Drawing unit, for according to the corresponding latitude and longitude information of suspect's motion video point position information, drawing described on map
Suspect's trace information sample corresponding suspect event trace information；
First acquisition unit, for according to described suspect's event trace information, obtaining described suspect's event trace information pair
All base sites positions information in the scope of activities answered.
10. the suspect's identity recognition device based on video big data according to claim 9 is it is characterised in that described
First extraction module, comprising:
Second acquisition unit, in the range of the activity time of described suspect, obtaining each described base sites position information
The mobile device of middle access；
Second searching unit, sets for from all mobile devices obtaining, searching the movement accessing all base sites positions information
Standby and described mobile device accesses the turn-on time of each base sites position information；
Screening subelement, is set with the movement of described suspect's event trace information match for filtering out from lookup result
Standby；
3rd searching unit, for the identification information according to described mobile device, searches institute in mobile device operator platform
State the corresponding authentication information of mobile device；
4th searching unit, for according to described authentication information, searching the suspect of coupling in public security big data platform
Identity information.
The 11. suspect's identity recognition devices based on video big data according to claim 10 are it is characterised in that also wrap
Include:
Second receiver module, for receiving the video data of image acquisition device transmission；
Second extraction module, the feature for extracting the moving target in each frame video image and described moving target respectively is believed
Breath；
Memory module, for being stored in the characteristic information of described moving target and described moving target in database, obtains
Described moving target property data base.
The 12. suspect's identity recognition devices based on video big data according to claim 11 are it is characterised in that described
Memory module, comprising:
Signal generating unit, for the characteristic information according to described moving target, generates the spy corresponding to moving target each described
Levy label；Described feature tag at least includes: activity time label, video point position information labels and figure and features characteristic information label；
Adding device, for being added to each feature tag generating in corresponding described moving target；
Memory cell, for all moving targets carrying described feature tag are stored in database.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610677700.3A CN106339428B (en) | 2016-08-16 | 2016-08-16 | Suspect's personal identification method and device based on video big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610677700.3A CN106339428B (en) | 2016-08-16 | 2016-08-16 | Suspect's personal identification method and device based on video big data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106339428A true CN106339428A (en) | 2017-01-18 |
| CN106339428B CN106339428B (en) | 2019-08-23 |
Family
ID=57824208
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610677700.3A Active CN106339428B (en) | 2016-08-16 | 2016-08-16 | Suspect's personal identification method and device based on video big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106339428B (en) |
Cited By (28)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107480246A (en) * | 2017-08-10 | 2017-12-15 | 北京中航安通科技有限公司 | A kind of recognition methods of associate people and device |
| CN108053354A (en) * | 2017-11-06 | 2018-05-18 | 国政通科技股份有限公司 | A kind of quick personnel's technique for delineating and device |
| CN108427930A (en) * | 2018-03-20 | 2018-08-21 | 广东云立方互动科技有限公司 | The method and system of identity identification information incidence relation are established based on mathematical statistics |
| CN108556764A (en) * | 2018-05-03 | 2018-09-21 | 李建营 | The police vehicle-mounted office system of one kind and method |
| CN108595606A (en) * | 2018-04-20 | 2018-09-28 | 广东亿迅科技有限公司 | Public security case space-time analysis method and device based on carrier data |
| CN109034055A (en) * | 2018-07-24 | 2018-12-18 | 北京旷视科技有限公司 | Portrait plotting method, device and electronic equipment |
| CN109086829A (en) * | 2018-08-14 | 2018-12-25 | 东方网力科技股份有限公司 | A kind of method and device that social population administers |
| CN109359570A (en) * | 2018-09-30 | 2019-02-19 | 广东***职业学院 | A kind of method of video personage identification |
| CN109598223A (en) * | 2018-11-26 | 2019-04-09 | 北京洛必达科技有限公司 | Method and apparatus based on video acquisition target person |
| CN109615573A (en) * | 2018-12-05 | 2019-04-12 | 武汉烽火众智数字技术有限责任公司 | Field staff based on big data flees about to commit crimes analysis method and system |
| CN110175217A (en) * | 2019-05-16 | 2019-08-27 | 武汉数矿科技股份有限公司 | It is a kind of for determining the perception data analysis method and device of suspect |
| CN110399525A (en) * | 2019-07-27 | 2019-11-01 | 广州伽利略网络科技有限公司 | A kind of people based on image recognition technology, object motion profile method for quickly retrieving |
| CN110650322A (en) * | 2019-10-29 | 2020-01-03 | 北京枭龙科技有限公司 | Security and protection system based on cloud service, Internet of things and AR security and protection glasses |
| CN110659580A (en) * | 2019-08-29 | 2020-01-07 | 深圳市新系区块链技术有限公司 | Method and device for quickly authenticating identity information |
| CN110825893A (en) * | 2019-09-18 | 2020-02-21 | 北京旷视科技有限公司 | Target searching method, device, system and storage medium |
| CN110856115A (en) * | 2019-11-28 | 2020-02-28 | 北京明略软件***有限公司 | Identification method and identification device for fraud organization offence area and electronic equipment |
| CN110942619A (en) * | 2018-09-21 | 2020-03-31 | 杭州海康威视***技术有限公司 | Vehicle determination method, device and system and electronic equipment |
| CN111079524A (en) * | 2019-11-05 | 2020-04-28 | 联通***集成有限公司贵州省分公司 | Target identity recognition method and system based on operator base station |
| WO2020103293A1 (en) * | 2018-11-22 | 2020-05-28 | 深圳云天励飞技术有限公司 | Method, device, and electronic device for presenting individual search information |
| WO2020134677A1 (en) * | 2018-12-26 | 2020-07-02 | 中兴通讯股份有限公司 | Unlawful advertisement processing method and apparatus, and computer-readable storage medium |
| CN111367955A (en) * | 2019-10-09 | 2020-07-03 | 杭州海康威视***技术有限公司 | Target object identification method and device, electronic equipment and storage medium |
| CN111898572A (en) * | 2020-08-05 | 2020-11-06 | 杭州云栖智慧视通科技有限公司 | Case intelligent serial-parallel method based on shape recognition |
| CN111935450A (en) * | 2020-07-15 | 2020-11-13 | 长江大学 | Intelligent suspect tracking method and system and computer readable storage medium |
| CN112182055A (en) * | 2019-07-02 | 2021-01-05 | ***通信集团贵州有限公司 | Suspect determination method, apparatus, device and storage medium |
| CN112256667A (en) * | 2020-09-16 | 2021-01-22 | 珠海市新德汇信息技术有限公司 | Multi-biological characteristic normalization method |
| CN112347296A (en) * | 2020-11-16 | 2021-02-09 | 罗普特科技集团股份有限公司 | Person and case association analysis method and device based on face recognition |
| CN112364683A (en) * | 2020-09-22 | 2021-02-12 | 苏州千视通视觉科技股份有限公司 | Case evidence fixing method and device |
| CN112800176A (en) * | 2020-12-23 | 2021-05-14 | 电信科学技术第十研究所有限公司 | Organization member mining method and device based on identity identification and terminal identification |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102929903A (en) * | 2012-07-04 | 2013-02-13 | 北京中盾安全技术开发公司 | Rapid video retrieval method based on layered structuralized description of video information |
| CN103716878A (en) * | 2013-12-12 | 2014-04-09 | 深圳先进技术研究院 | Method for locating with the use of mobile phone and video monitoring equipment |
| CN103914532A (en) * | 2014-03-31 | 2014-07-09 | 安徽新华博信息技术股份有限公司 | Analyzing method for automatically troubleshooting suspects |
| CN104034316A (en) * | 2013-03-06 | 2014-09-10 | 深圳先进技术研究院 | Video analysis-based space positioning method |
| CN104243926A (en) * | 2014-09-23 | 2014-12-24 | 深圳先进技术研究院 | Multi-source big data collection system for police |
| CN105427221A (en) * | 2015-12-09 | 2016-03-23 | 北京中科云集科技有限公司 | Cloud platform-based police affair management method |
-
2016
- 2016-08-16 CN CN201610677700.3A patent/CN106339428B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102929903A (en) * | 2012-07-04 | 2013-02-13 | 北京中盾安全技术开发公司 | Rapid video retrieval method based on layered structuralized description of video information |
| CN104034316A (en) * | 2013-03-06 | 2014-09-10 | 深圳先进技术研究院 | Video analysis-based space positioning method |
| CN103716878A (en) * | 2013-12-12 | 2014-04-09 | 深圳先进技术研究院 | Method for locating with the use of mobile phone and video monitoring equipment |
| CN103914532A (en) * | 2014-03-31 | 2014-07-09 | 安徽新华博信息技术股份有限公司 | Analyzing method for automatically troubleshooting suspects |
| CN104243926A (en) * | 2014-09-23 | 2014-12-24 | 深圳先进技术研究院 | Multi-source big data collection system for police |
| CN105427221A (en) * | 2015-12-09 | 2016-03-23 | 北京中科云集科技有限公司 | Cloud platform-based police affair management method |
Cited By (37)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107480246A (en) * | 2017-08-10 | 2017-12-15 | 北京中航安通科技有限公司 | A kind of recognition methods of associate people and device |
| CN107480246B (en) * | 2017-08-10 | 2021-03-12 | 北京中航安通科技有限公司 | Method and device for identifying associated personnel |
| CN108053354A (en) * | 2017-11-06 | 2018-05-18 | 国政通科技股份有限公司 | A kind of quick personnel's technique for delineating and device |
| CN108427930A (en) * | 2018-03-20 | 2018-08-21 | 广东云立方互动科技有限公司 | The method and system of identity identification information incidence relation are established based on mathematical statistics |
| CN108595606A (en) * | 2018-04-20 | 2018-09-28 | 广东亿迅科技有限公司 | Public security case space-time analysis method and device based on carrier data |
| CN108556764A (en) * | 2018-05-03 | 2018-09-21 | 李建营 | The police vehicle-mounted office system of one kind and method |
| CN109034055A (en) * | 2018-07-24 | 2018-12-18 | 北京旷视科技有限公司 | Portrait plotting method, device and electronic equipment |
| CN109086829A (en) * | 2018-08-14 | 2018-12-25 | 东方网力科技股份有限公司 | A kind of method and device that social population administers |
| CN110942619B (en) * | 2018-09-21 | 2024-03-08 | 杭州海康威视***技术有限公司 | Vehicle determination method, device, system and electronic equipment |
| CN110942619A (en) * | 2018-09-21 | 2020-03-31 | 杭州海康威视***技术有限公司 | Vehicle determination method, device and system and electronic equipment |
| CN109359570A (en) * | 2018-09-30 | 2019-02-19 | 广东***职业学院 | A kind of method of video personage identification |
| WO2020103293A1 (en) * | 2018-11-22 | 2020-05-28 | 深圳云天励飞技术有限公司 | Method, device, and electronic device for presenting individual search information |
| CN109598223A (en) * | 2018-11-26 | 2019-04-09 | 北京洛必达科技有限公司 | Method and apparatus based on video acquisition target person |
| CN109615573A (en) * | 2018-12-05 | 2019-04-12 | 武汉烽火众智数字技术有限责任公司 | Field staff based on big data flees about to commit crimes analysis method and system |
| CN109615573B (en) * | 2018-12-05 | 2023-05-05 | 武汉烽火众智数字技术有限责任公司 | Foreign personnel flow channeling analysis method and system based on big data |
| WO2020134677A1 (en) * | 2018-12-26 | 2020-07-02 | 中兴通讯股份有限公司 | Unlawful advertisement processing method and apparatus, and computer-readable storage medium |
| CN111368106B (en) * | 2018-12-26 | 2024-04-26 | 中兴通讯股份有限公司 | Method and device for processing wild advertisement and computer readable storage medium |
| CN111368106A (en) * | 2018-12-26 | 2020-07-03 | 中兴通讯股份有限公司 | Method and device for processing wild advertisements and computer readable storage medium |
| CN110175217A (en) * | 2019-05-16 | 2019-08-27 | 武汉数矿科技股份有限公司 | It is a kind of for determining the perception data analysis method and device of suspect |
| CN112182055A (en) * | 2019-07-02 | 2021-01-05 | ***通信集团贵州有限公司 | Suspect determination method, apparatus, device and storage medium |
| CN110399525A (en) * | 2019-07-27 | 2019-11-01 | 广州伽利略网络科技有限公司 | A kind of people based on image recognition technology, object motion profile method for quickly retrieving |
| CN110659580A (en) * | 2019-08-29 | 2020-01-07 | 深圳市新系区块链技术有限公司 | Method and device for quickly authenticating identity information |
| CN110825893A (en) * | 2019-09-18 | 2020-02-21 | 北京旷视科技有限公司 | Target searching method, device, system and storage medium |
| CN111367955B (en) * | 2019-10-09 | 2024-03-26 | 杭州海康威视***技术有限公司 | Target object identification method, target object identification device, electronic equipment and storage medium |
| CN111367955A (en) * | 2019-10-09 | 2020-07-03 | 杭州海康威视***技术有限公司 | Target object identification method and device, electronic equipment and storage medium |
| CN110650322A (en) * | 2019-10-29 | 2020-01-03 | 北京枭龙科技有限公司 | Security and protection system based on cloud service, Internet of things and AR security and protection glasses |
| CN111079524A (en) * | 2019-11-05 | 2020-04-28 | 联通***集成有限公司贵州省分公司 | Target identity recognition method and system based on operator base station |
| CN110856115A (en) * | 2019-11-28 | 2020-02-28 | 北京明略软件***有限公司 | Identification method and identification device for fraud organization offence area and electronic equipment |
| CN111935450A (en) * | 2020-07-15 | 2020-11-13 | 长江大学 | Intelligent suspect tracking method and system and computer readable storage medium |
| CN111898572A (en) * | 2020-08-05 | 2020-11-06 | 杭州云栖智慧视通科技有限公司 | Case intelligent serial-parallel method based on shape recognition |
| CN112256667A (en) * | 2020-09-16 | 2021-01-22 | 珠海市新德汇信息技术有限公司 | Multi-biological characteristic normalization method |
| CN112256667B (en) * | 2020-09-16 | 2024-03-22 | 珠海市新德汇信息技术有限公司 | Multi-biological characteristic normalization method |
| CN112364683A (en) * | 2020-09-22 | 2021-02-12 | 苏州千视通视觉科技股份有限公司 | Case evidence fixing method and device |
| CN112347296A (en) * | 2020-11-16 | 2021-02-09 | 罗普特科技集团股份有限公司 | Person and case association analysis method and device based on face recognition |
| CN112347296B (en) * | 2020-11-16 | 2022-06-17 | 罗普特科技集团股份有限公司 | Person and case association analysis method and device based on face recognition |
| CN112800176A (en) * | 2020-12-23 | 2021-05-14 | 电信科学技术第十研究所有限公司 | Organization member mining method and device based on identity identification and terminal identification |
| CN112800176B (en) * | 2020-12-23 | 2024-02-06 | 电信科学技术第十研究所有限公司 | Organization member mining method and device based on identity and terminal identification |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106339428B (en) | 2019-08-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106339428A (en) | Identity identification method and device for suspects based on large video data | |
| US10810870B2 (en) | Method of processing passage record and device | |
| CN102843547A (en) | Intelligent tracking method and system for suspected target | |
| CN111461089A (en) | Face detection method, and training method and device of face detection model | |
| US10725737B2 (en) | Address information-based account mapping method and apparatus | |
| Weng et al. | Towards understanding the security of modern image captchas and underground captcha-solving services | |
| CN107665289B (en) | Operator data processing method and system | |
| CN102868983B (en) | Data interactive method and system | |
| CN111930868A (en) | Big data behavior trajectory analysis method based on multi-dimensional data acquisition | |
| CN108765610A (en) | Attendance management method for work transmission line scene | |
| EP3828732A2 (en) | Method and apparatus for processing identity information, electronic device, and storage medium | |
| CN112770265B (en) | Pedestrian identity information acquisition method, system, server and storage medium | |
| CN105518644A (en) | Method for processing and displaying real-time social data on map | |
| WO2024106829A1 (en) | System for providing sports event operation management platform service | |
| CN112925899B (en) | Ordering model establishment method, case clue recommendation method, device and medium | |
| CN115376192B (en) | User abnormal behavior determination method, device, computer equipment and storage medium | |
| Cao et al. | Towards activity recognition through multidimensional mobile data fusion with a smartphone and deep learning | |
| CN115984643A (en) | Model training method, related device and storage medium | |
| CN114745558B (en) | Live broadcast monitoring method, device, system, equipment and medium | |
| CN102547678A (en) | Number portability short message log analysis method, system and device | |
| CN108122290A (en) | Intelligent polling method and device | |
| CN115062197A (en) | Attendance data detection method and device and storage medium | |
| CN112601182A (en) | Epidemic prevention traceability method based on WIFI probe | |
| CN110263082A (en) | The data distribution analysis method of database, device, electronic equipment and storage medium | |
| CN112837061B (en) | Data processing method and related device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| PP01 | Preservation of patent right | ||
| PP01 | Preservation of patent right |
Effective date of registration: 20220726 Granted publication date: 20190823 |