CN108960048A - A kind of searching method and system for the missing tourist in scenic spot based on big data - Google Patents
A kind of searching method and system for the missing tourist in scenic spot based on big data Download PDFInfo
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Abstract
The invention discloses a kind of based on big data is missing the searching method and system of tourist for scenic spot, wherein described search method includes: recognition of face, scenery identification and establishes tourist's network of personal connections.Described search system includes: cloud service platform and data acquisition subsystem, the cloud service platform includes: face recognition module, scene features extraction module, track generation module and information storage module again, and the data acquisition subsystem includes: identity information acquisition module, image capture module, navigation module, pedometer module, communication module and voice module again.The present invention enables it to more easily be received by tourist, improves utilization rate of the invention by the way that such as, functions, the subtle information to scenic spot such as scenery identification, sight spot navigation are collected, to reach preferable search purpose.In addition, push missing crew message of the present invention by network of personal connections selectivity, largely utilizes tourist's resource, avoids the waste of manpower.
Description
Technical field
The present invention relates to big data search fields, are used for the missing tourist in scenic spot based on big data more particularly to a kind of
Searching method and system, for solve such as scenic spot place missing crew search or auxiliary search and rescue.
Background technique
In recent years, increasing with tourist arrivals, tourist attractions personnel are missing or the case of children loss is commonplace,
Especially natural scenic spots, area coverage is big, complex geographical environment, once there is personnel missing, especially children, or lose
Join situation, search-and-rescue work is difficult effectively to be unfolded, and generally requires to spend a large amount of manpower and material resources, and due to lacking missing crew's
Disappeared position information causes its search efficiency not high, and the search and rescue time is longer, these are all very for children or tourist in danger
Unfavorable.
The search based on big data currently on the market, the main video by obtaining in monitoring camera, in video
Image intercept to realize search to related personnel, but camera is set up in natural scenic spots first is that it set up
Cheng Buyi, and the every nook and cranny at scenic spot can not be spread, later period maintenance management is also more difficult, second is that, to its collected figure
As without a kind of reasonable processing method, be quickly and effectively missing regional prediction to missing crew for scenic spot.Third is that existing
The some hardware or method for scenic spot search having, have a single function, and do not have entertainment or other utility functions, because
This causes its tourist's service efficiency very low, therefore also causes it not high to the search efficiency of missing crew.
Summary of the invention
For above content, disclose according to an aspect of the present invention it is a kind of based on big data for the missing trip in scenic spot
The searching method of visitor, comprising: obtain missing crew's information；Determine before missing crew is missing occur place for the last time；To missing
Personnel's image interior for a period of time carries out image information extraction, and identifies to information progress big data comparison is extracted；According to missing
The travel speed of image information assessment missing crew before personnel are missing；There is place and the traveling according to the last time
The possibility region of evaluation of speed missing crew；Opening relationships net carries out sea of faces's knowledge to missing crew by the network of personal connections
Not, to further reduce the possibility region of missing crew.
Further, the personal information includes: that facial image information, age, gender and trip are intended to.
Further, described image information extraction includes: the scene image and character image in image.
Further, the character image includes: facial image or the dress ornament image of personage.
Further, it includes: by calculating the scene image that described pair of extraction information, which carries out big data comparison identification,
Or the mode of the dress ornament image cryptographic Hash carries out big data comparison to the cryptographic Hash of scenery or dress ornament, to carry out scenery or clothes
The identification of decorations, wherein further including the color of dress ornament to the identification of dress ornament；By the method based on local binary patterns to face figure
As carrying out feature extraction, the feature is compared using big data, to carry out recognition of face.
Further, the opening relationships net include: to missing crew before missing last time occur the image in place into
Facial image in row image carries out recognition of face, obtains level-one affiliated person, and wherein level-one affiliated person can be one or more；
The pertinent image information for obtaining above-mentioned level-one affiliated person carries out big data face to the facial image in the pertinent image information
Identification obtains second level affiliated person, wherein second level affiliated person can be one or more；And so on, obtain respiratory sensation people's
Image information, thus opening relationships net.
Further, it is compared by carrying out face to the respiratory sensation people and missing crew, to be lost
The sea of faces of track personnel identifies.
According to another aspect of the present invention, it discloses a kind of using above-mentioned a kind of missing for scenic spot based on big data
The search system of the searching method of tourist, comprising: data acquisition subsystem and cloud service platform, wherein data acquisition system
System has multiple functions, and the cloud service platform is for identifying scenery, face and dress ornament, the data acquisition system
System is wirelessly communicated with the cloud service platform.
Preferably, the data acquisition subsystem includes: identity information acquisition module, and the identity for acquiring tourist is believed
Breath；Image capture module carries out Image Acquisition for starting shooting function；Navigation module: the path navigation for target scenic spot；
Pedometer module is counted for the step number to user；Communication module is corresponding for establishing communication acquisition to cloud service platform
Information, or receive the prompting message from cloud service platform；Voice module is used for voice broadcast.
Preferably, the cloud service platform includes: face recognition module, for mentioning to the facial image in image
It takes, and carries out recognition of face；Scene features extraction module carries out scenery identification for extracting to the scenery in image；Rail
Mark generation module, for according in image information location information and temporal information generate travel track, and combined use person
Travel speed and be intended to estimation user region；Information storage module, for tourist information extraction, classification and
It saves.
It is an advantage of the invention that system or method tourist's network of personal connections can be established through the invention, to pass through network of personal connections pair
The travelling route of missing tourist and final possibility region predict that method is simple, and it is convenient that system is established, very great Cheng
The existing resource in scenic spot is utilized on degree, by some simple and practical functions, e.g., the functions such as scenery identification, sight spot navigation are dived
Being collected to the information at scenic spot for silentization is moved, enables it to more be received by tourist, so that present system or method
Utilization rate it is higher, to reach preferable search purpose, in addition, the network of personal connections established through the invention, selectively pushes
The information of missing crew avoids the waste of resource during message cluster transmition, thereby increases and it is possible to influence the feelings of the utilization rate of user
Condition, this human resources of a large amount of tourists are utilized to the full extent, to wander away to solve general lost contact or children
Situation, while a large amount of utilizations to other tourist informations also provide for difficult search-and-rescue work with big convenience.
Detailed description of the invention
By reading the detailed description of following detailed description, various other advantages and benefits are common for this field
Technical staff will become clear.Attached drawing is only used for showing the purpose of specific embodiment, and is not considered as to the present invention
Limitation.And throughout the drawings, the same reference numbers will be used to refer to the same parts.In the accompanying drawings:
Fig. 1 shows a kind of method composition figure of missing crew's localization method based on big data of the present invention.
Fig. 2 shows a kind of search system structure charts for the missing tourist in scenic spot based on big data of the invention.
Fig. 3 shows cloud service platform in a kind of search system of the tourist that is missing for scenic spot based on big data of the present invention
Image processing flow figure.
Fig. 4 shows cloud service platform in a kind of search system of the tourist that is missing for scenic spot based on big data of the present invention
Positioning work flow diagram.
Fig. 5 is a kind of alternative embodiment of the invention, shows a kind of missing crew search and rescue side using present system
The flow chart of method.
Specific embodiment
The illustrative embodiments of the disclosure are more fully described below with reference to accompanying drawings.Although showing this public affairs in attached drawing
The illustrative embodiments opened, it being understood, however, that may be realized in various forms the disclosure without the reality that should be illustrated here
The mode of applying is limited.It is to be able to thoroughly understand the disclosure on the contrary, providing these embodiments, and can be by this public affairs
The range opened is fully disclosed to those skilled in the art.
As shown in Figure 1, forming figure for a kind of method of missing crew's localization method based on big data of the present invention, comprising:
S1, missing crew's information is obtained；S2, determine before missing crew is missing occur place for the last time；S3, to one section of missing crew when
Interior image carries out image information extraction, and identifies to information progress big data comparison is extracted；S4, it is missing according to missing crew
The travel speed of preceding image information assessment missing crew；S5, place and the travel speed are occurred according to the last time
Assess the possibility region of missing crew；S6, opening relationships net carry out sea of faces's knowledge to missing crew by the network of personal connections
Not, to further reduce the possibility region of missing crew.
Specifically, wherein missing crew's information includes, image information, age, gender and the trip of missing crew
It is intended to.Due to typically containing the temporal information and location information of image taking in present image information, pass through image
Temporal information in information judges the time and place that missing crew's last time occurs, for not including position in image
, it can be by being extracted to the scenery in image, and identification comparison is carried out by big data, so that it is determined that the position of the image
Confidence breath.The image information being missing in for the previous period in the method for the present invention by obtaining missing crew, according to the time therein
Information and location information draw the activity trajectory of missing crew；At the same time, the travel speed of missing crew is calculated,
To deduce missing crew in travel speed in different time periods；Finally combine its trip intention and last travel speed
Judge the zone of action of missing crew.In addition, the present invention utilizes network of personal connections pair also by by establishing the network of personal connections between tourist
Tourist carries out sea of faces's search, to further reduce the zone of action range of missing tourist.Wherein, the method for building up of the network of personal connections
It include: to carry out the facial image in image to missing crew's image that place occurs in last time before missing to carry out recognition of face,
Level-one affiliated person is obtained, wherein level-one affiliated person can be one or more；Obtain the associated picture letter of above-mentioned level-one affiliated person
Breath carries out recognition of face to the facial image in the pertinent image information, obtains second level affiliated person, wherein second level affiliated person
It can be one or more；And so on, the image information of respiratory sensation people is obtained, thus opening relationships net.In network of personal connections
In establishment process, technological means that the present invention uses is face recognition technology, by using local binary patterns in the present invention
Method extracts face features.
LBP (Local Binary Pattern, local binary patterns) is that one kind is used to describe image local textural characteristics
Operator；It has the advantages that rotational invariance and gray scale invariance etc. are significant.LBP operator definitions are in the window of 3*3
The gray value of 8 adjacent pixels is compared by adjacent 8 pixels using window center pixel as threshold value with it, if surrounding
Grey scale pixel value is greater than center pixel gray value, then the position of the pixel is marked as 1, is otherwise 0.In this way, in 3*3 neighborhood
8 points compared and can produce 8 bits (being typically converted into decimal number i.e. LBP code, totally 256 kinds) to get to the window
The LBP value of mouthful central pixel point, and reflect with this value the texture information in the region, LBP is reduced into finally by by LBP value
Image compares two width LBP images by the methods of chi-square statistics, carries out recognition of face according to its similar programs.
It is illustrated in figure 2, the present invention goes sight-seeing the structure chart of navigation system, and search system of the present invention includes cloud service platform
And data acquisition subsystem, wherein (e.g., cloud service platform is used for storage, classification and the image processing work of tourist's data
Object Filtering identification, face extraction identification etc.), data acquisition subsystem can be using search system corresponding A PP's of the present invention
The equipment such as smart phone or Pad, data acquisition subsystem of the present invention not only make the main acquisition subsystem of search system of the present invention,
More in order to improve its utilization rate, and then improve the ability of acquisition data, the data acquisition subsystem further include: sight spot identification,
The functions such as sight spot navigation, voice broadcast, to stimulate the use of tourist.
Specifically, wherein cloud service platform includes face recognition module, scene features extraction module, track generation module
And information storage module.Wherein, face recognition module for extracting to the facial image in image, know by pedestrian's face of going forward side by side
Not；The function of face recognition module can be divided into two kinds, first is that the extraction of facial image, mentions the facial image in image
It takes；Second is that recognition of face, carries out recognition of face to the facial image of extraction.The process of recognition of face is in the introduction of above-mentioned Fig. 1
Hear character separation device method is used it has been already mentioned that the extracting method of the facial image, in the present invention to the people in image
Face face-image extracts.Scene features extraction module carries out scenery identification for extracting to the scenery in image；
It is used to identify that substantially process is as follows to scenery in described image information using the method that cryptographic Hash compares in the present invention:
Firstly, reducing dimension of picture, picture is reduced into the size with 64 pixels；Then simplify color, convert 64 for picture
Grade gray scale；Then average value is calculated, and the gray scale of each pixel is compared with average value, more than or equal to being denoted as average value
1,0 is denoted as less than the average value；And then the cryptographic Hash of the scenery is calculated, eventually by big data by the Kazakhstan of the scenery
Uncommon value is compared with the cryptographic Hash of known scenery, to identify to the scenery.In addition, search system of the present invention, may be used also
The other feature of missing crew, such as dress ornament, article worn are identified using same method, thus quickly diminution pair
The range of missing crew's progress recognition of face.Track generation module is advanced for being generated according to the location information in image information
Track, and the zone of action of the travel speed of combined use person and intention (interest sight spot) assessment user.Track generates mould
Block, for according in image information location information and temporal information generate travel track, and combined use person traveling speed
Degree and intention estimation user region；Information storage module, extraction, classification and preservation for tourist information.
The data acquisition subsystem includes: identity information acquisition module, for acquiring the identity information of tourist；In tourist
Before data acquisition subsystem of the present invention, tourist need to obtain use by filling in the information such as personal information and interest sight spot
Power.Wherein personal information includes gender, age and head portrait (face-image), image capture module, for starting shooting function
Carry out Image Acquisition；On the one hand the one side of the module can simply scheme the photo of shooting for starting shooting function
As processing, such as is scribbled to image, adds scene stage property.In addition, when containing the mark scape that can be identified in shooting image
When object, this subsystem can carry out on-line search by cloud service platform, and introduction relevant to the scenery is passed through voice broadcast
Module is broadcasted, so that the history culture at tourist's sound scape and the understanding of the cyclopentadienyl sight spot.Navigation module: it leads in the path for sight spot
Boat；Tourist can carry out route guidance by data sight spot related with foreground zone is worked as, in addition, the module will also pass through tourist's data
Sight spot information and then can be carried out with the track generation module in cloud service platform so that obtaining the tourist goes sight-seeing intention
Cooperate the possibility travelling route so that it is determined that missing crew, and combine the average travel speed of the missing crew, evaluates the mistake
The scope of activities of track tourist.Pedometer module is counted for the step number to user；The module can provide for cloud service platform
The activity condition of missing tourist.Communication module obtains corresponding information for communicating with cloud service platform foundation, or receives to come from cloud
The prompting message of service platform；Voice module is used for voice broadcast.
As shown in figure 3, for a kind of cloud service in the search system of tourist that is missing for scenic spot based on big data of the present invention
The image processing flow figure of platform.Cloud service platform can be to the communication equipment information together when obtaining the identity information of the tourist
It records, directly utilizes this by identifying that the sending device information of the reception information just may know that the source of the information later
Kind method associates the image information of acquisition with tourist information, when cloud service platform receives the figure uploaded from the tourist
When as information, identification will be extracted to the scene information in the image information respectively, people information therein can choose
Property extraction classification, such as children and adult, children (can be distinguished) by the size of its height or facial image, may be used also
It is described further with increasing such as clothes with clothing color information.The above process can be considered as the basic information of image and mention
It takes, it can be to be required to carry out to carry out the special tourist information of active collection (such as children) before detailed recognition of face, to work as this
When missing phenomenon occurs for class special population, range needed for can quickly reducing recognition of face, even without progress face knowledge
Missing crew can not directly not identified by artificially identifying.
As shown in figure 4, for a kind of cloud service in the search system of tourist that is missing for scenic spot based on big data of the present invention
The positioning work flow diagram of platform.When receive tourist be missing information after, need to determine missing tourist information first, its surname can be passed through
Name, photo or phone number etc. determine missing crew's information, by extract the missing crew last time upload image in when
Between information and location information, thus obtain missing crew last time there is place, can by obtain the personnel be missing it is previous
The image information of section time, or image information is uploaded just for last time, personage therein is extracted, can will wherein be known
Others' member's (using present system personnel) obtains institute by carrying out big data lookup in cloud platform as level-one affiliated person
State level-one affiliated person missing crew it is missing for the previous period or it is missing after a period of time upload image, and in image can
Identification personage extracts, as second level affiliated person.By recognition of face to the second level affiliated person carry out sign extraction and
Big data compares, to judge whether there is missing crew in the second level affiliated person, if obtaining the figure comprising missing crew
The location information and temporal information of picture, and continue to be associated with artificial lookup object with second level, three-level affiliated person is obtained, go forward side by side pedestrian
Face identification judgement, if obtaining the location information and temporal information of the image comprising missing crew, in this process, if
Missing crew is special personnel, such as children, can also be by increasing information such as, and clothes or clothing color are to reduce recognition of face
Range, to accelerate search speed.The present invention can inquire series by limitation affiliated person to terminate query process.
Embodiment
As shown in figure 5, being a kind of embodiment process of missing crew's rescue method, missing person is evaluated in cloud service platform
The zone of action range of member selectively the tourist into the region can send the missing message notifying of personnel, wherein message mentions
Show the identity information comprising missing tourist or the identity information and contact method of contact person, at this point, will also be accompanied by voice mould
The casting of block is reminded；The tourist for receiving the message searches for nearby according to the identity information of missing crew, if searching out missing person
Member can contact by the contact method in prompting message and with contact person.Among the above, missing crew and someone can be passed through
The number occurred jointly judges the degree of association, to carry out selectively sending message.
It should be noted that situations such as possibility situation of missing crew herein includes: lost contact, children loss.
More than, illustrative specific embodiment only of the invention, but scope of protection of the present invention is not limited thereto, appoints
In the technical scope disclosed by the present invention, any changes or substitutions that can be easily thought of, all by what those familiar with the art
It is covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be subject to the protection scope in claims.
Claims (10)
1. a kind of searching method for the missing tourist in scenic spot based on big data characterized by comprising
Obtain missing crew's information；
Determine before missing crew is missing occur place for the last time；
Image information extraction is carried out to missing crew's image interior for a period of time, and carries out big data comparison knowledge to information is extracted
Not；
According to the travel speed of image information assessment missing crew of the missing crew before missing；
Occurs the possibility region in place and travel speed assessment missing crew according to the last time；
Opening relationships net carries out sea of faces's identification to missing crew by the network of personal connections, to further reduce missing crew's
Possible region.
2. the method according to claim 1, wherein the personal information include: facial image information, the age,
Gender and trip are intended to.
3. the method according to claim 1, wherein described image information extraction includes: the scenery figure in image
Picture and character image.
4. according to the method described in claim 3, it is characterized in that, the character image includes: facial image or the clothes of personage
Adorn image.
5. the method according to claim 1, wherein described pair of extraction information carries out big data comparison identification packet
It includes:
The cryptographic Hash of scenery or dress ornament is carried out by way of calculating the scene image or the dress ornament image cryptographic Hash big
Data comparison, so that the identification of scenery or dress ornament is carried out, wherein further including the color of dress ornament to the identification of dress ornament；
Feature extraction is carried out to facial image by the method based on local binary patterns, the feature is carried out using big data
Comparison, to carry out recognition of face.
6. the method according to claim 1, wherein the opening relationships net includes:
Facial image in image is carried out to missing crew's image that place occurs in last time before missing and carries out recognition of face, is obtained
Level-one affiliated person is obtained, wherein level-one affiliated person can be one or more；
The pertinent image information for obtaining above-mentioned level-one affiliated person carries out big data to the facial image in the pertinent image information
Recognition of face obtains second level affiliated person, wherein second level affiliated person can be one or more；
And so on, the image information of respiratory sensation people is obtained, thus opening relationships net.
7. according to the method described in claim 6, it is characterized in that, by carrying out people to the respiratory sensation people and missing crew
Face compares, to carry out sea of faces's identification of missing crew.
8. a kind of be missing tourist's for scenic spot based on big data using a kind of described in the claims 1-7 any one
The system of searching method characterized by comprising data acquisition subsystem and cloud service platform, wherein data acquisition system
System has multiple functions, and the cloud service platform is for identifying scenery, face and dress ornament, the data acquisition system
System is wirelessly communicated with the cloud service platform.
9. system according to claim 8, which is characterized in that the data acquisition subsystem includes:
Identity information acquisition module, for acquiring the identity information of tourist；
Image capture module carries out Image Acquisition for starting shooting function；
Navigation module: the path navigation for target scenic spot；
Pedometer module is counted for the step number to user；
Communication module obtains corresponding information for communicating with cloud service platform foundation, or receives the message from cloud service platform
It reminds；
Voice module is used for voice broadcast.
10. system according to claim 8, which is characterized in that the cloud service platform includes:
Face recognition module for extracting to the facial image in image, and carries out recognition of face；
Scene features extraction module carries out scenery identification for extracting to the scenery in image；
Track generation module, for according in image information location information and temporal information generate travel track, and combine
The travel speed of user and intention estimation user region；
Information storage module, extraction, classification and preservation for tourist information.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109684494A (en) * | 2018-12-27 | 2019-04-26 | 爱笔（北京）智能科技有限公司 | A kind of scenic spot looking-for-person method, system and cloud server |
| CN110633656A (en) * | 2019-08-29 | 2019-12-31 | 恒大智慧科技有限公司 | Scenic spot person-searching information publishing method and system and storage medium |
| CN110781265A (en) * | 2019-10-28 | 2020-02-11 | 恒大智慧科技有限公司 | Scenic spot person searching method and device and storage medium |
| CN112434626A (en) * | 2020-11-30 | 2021-03-02 | 吉林建筑大学 | Method and device for monitoring position of vision-impaired person in scenic spot |
| CN112949396A (en) * | 2021-01-29 | 2021-06-11 | 南通大学 | Self-adaptive method for searching co-trip personnel in scenic spot |
| CN113132680A (en) * | 2019-12-31 | 2021-07-16 | 浙江宇视科技有限公司 | Method, apparatus, device and medium for preventing person from missing |
| CN113449714A (en) * | 2021-09-02 | 2021-09-28 | 深圳奥雅设计股份有限公司 | Face recognition method and system for child playground |
| CN116912899A (en) * | 2023-05-22 | 2023-10-20 | 国政通科技有限公司 | Personnel searching method and device based on regional network |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101989300A (en) * | 2010-10-15 | 2011-03-23 | 江苏省莱科信息技术有限公司 | Missing person seeking system and implementation method for seeking missing person |
| KR20110062381A (en) * | 2009-12-03 | 2011-06-10 | 심영도 | System for crime prevention and tracking missing person by using vehicle shooting film |
| CN102843547A (en) * | 2012-08-01 | 2012-12-26 | 安科智慧城市技术（中国）有限公司 | Intelligent tracking method and system for suspected target |
| JP2013109685A (en) * | 2011-11-24 | 2013-06-06 | Zenrin Datacom Co Ltd | Search object searching support system and search object searching support program |
| US20160104121A1 (en) * | 2014-10-10 | 2016-04-14 | Benjamin Garner | Digital Flyer Service |
| CN105992138A (en) * | 2015-01-29 | 2016-10-05 | 深圳好父母婴幼儿用品有限公司 | People searching system and method |
| JP2017045218A (en) * | 2015-08-26 | 2017-03-02 | 株式会社Ｂ−Ｐｒｏｓｔ | Stray child prevention system using transmitter capable of short-range wireless communication |
| CN106920256A (en) * | 2017-03-14 | 2017-07-04 | 上海琛岫自控科技有限公司 | A kind of effective missing child searching system |
| CN206340065U (en) * | 2016-10-25 | 2017-07-18 | 哈尔滨工业大学深圳研究生院 | A kind of Missing Persons' searching system based on face recognition technology |
| CN106960172A (en) * | 2016-01-08 | 2017-07-18 | 中兴通讯股份有限公司 | Personal identification processing method, apparatus and system |
| CN107195018A (en) * | 2017-05-17 | 2017-09-22 | 金碧凡 | A kind of front end big data vehicle intelligent system |
| CN107705224A (en) * | 2017-08-28 | 2018-02-16 | 深圳市赛亿科技开发有限公司 | A kind of guidance method and system based on AR glasses |
| CN107845234A (en) * | 2017-11-27 | 2018-03-27 | 浙江卓锐科技股份有限公司 | A kind of anti-anti- method of wandering away of system and scenic spot of wandering away in scenic spot |
| CN107977421A (en) * | 2017-11-24 | 2018-05-01 | 泰华智慧产业集团股份有限公司 | The method and device of fake-licensed car analysis is carried out based on big data |
-
2018
- 2018-05-23 CN CN201810500470.2A patent/CN108960048B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20110062381A (en) * | 2009-12-03 | 2011-06-10 | 심영도 | System for crime prevention and tracking missing person by using vehicle shooting film |
| CN101989300A (en) * | 2010-10-15 | 2011-03-23 | 江苏省莱科信息技术有限公司 | Missing person seeking system and implementation method for seeking missing person |
| JP2013109685A (en) * | 2011-11-24 | 2013-06-06 | Zenrin Datacom Co Ltd | Search object searching support system and search object searching support program |
| CN102843547A (en) * | 2012-08-01 | 2012-12-26 | 安科智慧城市技术（中国）有限公司 | Intelligent tracking method and system for suspected target |
| US20160104121A1 (en) * | 2014-10-10 | 2016-04-14 | Benjamin Garner | Digital Flyer Service |
| CN105992138A (en) * | 2015-01-29 | 2016-10-05 | 深圳好父母婴幼儿用品有限公司 | People searching system and method |
| JP2017045218A (en) * | 2015-08-26 | 2017-03-02 | 株式会社Ｂ−Ｐｒｏｓｔ | Stray child prevention system using transmitter capable of short-range wireless communication |
| CN106960172A (en) * | 2016-01-08 | 2017-07-18 | 中兴通讯股份有限公司 | Personal identification processing method, apparatus and system |
| CN206340065U (en) * | 2016-10-25 | 2017-07-18 | 哈尔滨工业大学深圳研究生院 | A kind of Missing Persons' searching system based on face recognition technology |
| CN106920256A (en) * | 2017-03-14 | 2017-07-04 | 上海琛岫自控科技有限公司 | A kind of effective missing child searching system |
| CN107195018A (en) * | 2017-05-17 | 2017-09-22 | 金碧凡 | A kind of front end big data vehicle intelligent system |
| CN107705224A (en) * | 2017-08-28 | 2018-02-16 | 深圳市赛亿科技开发有限公司 | A kind of guidance method and system based on AR glasses |
| CN107977421A (en) * | 2017-11-24 | 2018-05-01 | 泰华智慧产业集团股份有限公司 | The method and device of fake-licensed car analysis is carried out based on big data |
| CN107845234A (en) * | 2017-11-27 | 2018-03-27 | 浙江卓锐科技股份有限公司 | A kind of anti-anti- method of wandering away of system and scenic spot of wandering away in scenic spot |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109684494A (en) * | 2018-12-27 | 2019-04-26 | 爱笔（北京）智能科技有限公司 | A kind of scenic spot looking-for-person method, system and cloud server |
| CN110633656A (en) * | 2019-08-29 | 2019-12-31 | 恒大智慧科技有限公司 | Scenic spot person-searching information publishing method and system and storage medium |
| CN110781265A (en) * | 2019-10-28 | 2020-02-11 | 恒大智慧科技有限公司 | Scenic spot person searching method and device and storage medium |
| CN113132680A (en) * | 2019-12-31 | 2021-07-16 | 浙江宇视科技有限公司 | Method, apparatus, device and medium for preventing person from missing |
| CN112434626A (en) * | 2020-11-30 | 2021-03-02 | 吉林建筑大学 | Method and device for monitoring position of vision-impaired person in scenic spot |
| CN112434626B (en) * | 2020-11-30 | 2022-08-02 | 吉林建筑大学 | Method and device for monitoring position of vision-impaired person in scenic spot |
| CN112949396A (en) * | 2021-01-29 | 2021-06-11 | 南通大学 | Self-adaptive method for searching co-trip personnel in scenic spot |
| CN112949396B (en) * | 2021-01-29 | 2023-11-24 | 南通大学 | Self-adaptive method for searching for people on the same trip in scenic spot |
| CN113449714A (en) * | 2021-09-02 | 2021-09-28 | 深圳奥雅设计股份有限公司 | Face recognition method and system for child playground |
| CN113449714B (en) * | 2021-09-02 | 2021-12-28 | 深圳奥雅设计股份有限公司 | Identification method and system for child playground |
| CN116912899A (en) * | 2023-05-22 | 2023-10-20 | 国政通科技有限公司 | Personnel searching method and device based on regional network |
| CN116912899B (en) * | 2023-05-22 | 2024-05-03 | 国政通科技有限公司 | Personnel searching method and device based on regional network |
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