CN114708696A - Elevator car stealing behavior monitoring method and system based on upper limb micro-motion recognition - Google Patents

Elevator car stealing behavior monitoring method and system based on upper limb micro-motion recognition Download PDF

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CN114708696A
CN114708696A CN202210340407.3A CN202210340407A CN114708696A CN 114708696 A CN114708696 A CN 114708696A CN 202210340407 A CN202210340407 A CN 202210340407A CN 114708696 A CN114708696 A CN 114708696A
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micro
gesture
upper limb
image
elevator car
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CN114708696B (en
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张彦波
陈明月
王多峰
朱袆
谷沣洋
万子伦
迈克·克拉维齐
张杨
张锦龙
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Henan University
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B13/00—Burglar, theft or intruder alarms
    • G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
    • G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
    • G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
    • G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
    • G08B13/19602—Image analysis to detect motion of the intruder, e.g. by frame subtraction
    • G08B13/19613—Recognition of a predetermined image pattern or behaviour pattern indicating theft or intrusion
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/70—Denoising; Smoothing
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B13/00—Burglar, theft or intruder alarms
    • G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
    • G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
    • G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
    • G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
    • G08B13/19639—Details of the system layout
    • G08B13/19645—Multiple cameras, each having view on one of a plurality of scenes, e.g. multiple cameras for multi-room surveillance or for tracking an object by view hand-over
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B3/00—Audible signalling systems; Audible personal calling systems
    • G08B3/10—Audible signalling systems; Audible personal calling systems using electric transmission; using electromagnetic transmission
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B50/00—Energy efficient technologies in elevators, escalators and moving walkways, e.g. energy saving or recuperation technologies

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Data Mining & Analysis (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Evolutionary Biology (AREA)
  • Evolutionary Computation (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • General Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Electromagnetism (AREA)
  • Indicating And Signalling Devices For Elevators (AREA)
  • Maintenance And Inspection Apparatuses For Elevators (AREA)

Abstract

The invention provides an elevator car stealing behavior monitoring method and system based on upper limb micro-action recognition. The method comprises the following steps of 1: obtaining passenger video stream information in an elevator car under a plurality of angles; step 2: framing the passenger video stream information, and performing image preprocessing on each frame of image; and step 3: performing head and arm posture recognition on the preprocessed image, and judging the type of the limb micro-motion; detecting whether predefined gesture postures exist in the image or not; judging whether suspected theft exists or not by combining the judgment result of the micro-action category of the limb and the detection result of the gesture; and 4, step 4: and if suspected theft exists, generating a voice reminding instruction so as to carry out voice reminding. The invention can effectively reduce the crime rate of the closed space theft, and simultaneously better remind the public to protect the property safety of the public.

Description

Elevator car stealing behavior monitoring method and system based on upper limb micro-motion recognition
Technical Field
The invention relates to the technical field of intelligent monitoring, in particular to a method and a system for monitoring elevator car stealing behavior based on upper limb micro-motion recognition.
Background
The elevator is always a target place for stealing due to the problems of large number of users, closed space, serious shielding and the like. In China, articles are very easy to steal in an elevator or at the moment of entering the elevator, particularly in the elevators in markets, hospitals and other places. Every time an elevator stealing and detecting case needs to consume a great deal of police force, financial resources and energy, and meanwhile, the stealing behavior in the elevator is a threat to the property safety of the public.
Therefore, the elevator system capable of identifying the stealing behavior and giving the voice alarm can greatly reduce the stealing crime rate of the closed space and better remind the public to protect the property safety of the public.
Disclosure of Invention
The invention provides an elevator car stealing behavior monitoring method and system based on upper limb micro-action recognition, aiming at overcoming the problem of crowd shielding in an elevator car and better recognizing stealing behavior.
On one hand, the invention provides an elevator car stealing behavior monitoring method based on upper limb micro-action recognition, which comprises the following steps:
step 1: obtaining passenger video stream information in an elevator car under a plurality of angles;
step 2: framing the passenger video stream information, and performing image preprocessing on each frame of image;
and 3, step 3: performing head and arm posture recognition on the preprocessed image, and judging the type of the limb micro-motion; detecting whether a predefined gesture exists in the image; judging whether suspected theft exists or not by combining the judgment result of the micro-action category of the limb and the detection result of the gesture;
and 4, step 4: and if suspected theft exists, generating a voice reminding instruction so as to carry out voice reminding.
Further, the image preprocessing at least comprises: graying, image smoothing, binarization and morphological processing.
Further, step 3 specifically includes:
extracting limb micro-motion characteristic parameters and gesture posture characteristic parameters from the image, and forming upper limb micro-motion vectors based on the extracted characteristic parameters;
and comparing the similarity of the upper limb micro-motion vector with the upper limb micro-motion vector in the stealing template library, and taking the gesture category corresponding to the upper limb micro-motion vector in the stealing module with the highest similarity as the detection result of the gesture posture.
Further, in step 3, when performing gesture recognition on the head and the arms, the extracted limb micro-motion characteristic parameters include: the swing amplitude of the head, the longitudinal extension amplitude of the arm and the transverse cutting amplitude of the arm.
Further, in step 3, when detecting the gesture posture, the extracted gesture posture characteristic parameters include: a rectangle width to height ratio of the gesture periphery, a shape ratio, a perimeter of the gesture, and a gesture area.
On the other hand, the invention provides an elevator car stealing behavior monitoring system based on upper limb micro-action recognition, which comprises:
the information acquisition module is used for acquiring passenger video stream information in the elevator car under a plurality of angles;
the image preprocessing module is used for framing the passenger video stream information and preprocessing images of each frame;
the upper limb micro-motion recognition module is used for recognizing the postures of the head and the arms of the preprocessed image and judging the classes of the limb micro-motion; detecting whether a predefined gesture exists in the image; judging whether suspected theft exists or not by combining the judgment result of the micro-action category of the limb and the detection result of the gesture;
and the control module is used for generating a voice alarm instruction and sending the voice alarm instruction to the voice reminding module for voice reminding when suspected theft exists.
Further, the information acquisition module comprises a plurality of image collectors; the image collectors are respectively arranged on the top of the elevator car and the peripheral side walls.
Furthermore, the upper limb fine motion recognition module comprises a limb recognition unit, a gesture recognition unit and a judgment unit;
the limb identification unit is used for extracting limb micro-motion characteristic parameters from the image;
the gesture recognition unit is used for extracting gesture feature parameters from the image;
and the judging unit is used for forming an upper limb micro-motion vector according to the extracted parameters, comparing the similarity of the upper limb micro-motion vector with the upper limb micro-motion vector in the stealing template library, and taking the gesture category corresponding to the upper limb micro-motion vector in the stealing module with the highest similarity as the detection result of the gesture posture.
Further, the system also comprises a power supply module; and the power supply module is connected with other modules.
Further, the system also comprises a power supply detection module for detecting the electric quantity of the power supply module, and when the detected electric quantity is lower than the threshold electric quantity, an alarm is given out.
The invention has the beneficial effects that:
the elevator car stealing behavior monitoring method and system based on upper limb micro-motion recognition, provided by the invention, are characterized in that the clearest limb and gesture video data streams of a human body in an elevator car are obtained through a plurality of image information collectors positioned in the elevator car, then, after the steps of gray processing, image smoothing, binarization processing, morphological processing and the like are carried out on each frame of image of the video streams, each frame of processed image is transmitted to an upper limb micro-motion recognition module. The upper limb micro-motion recognition module comprises two recognition units: the body recognition unit and the gesture recognition unit comprehensively judge whether suspected pickpocket behavior exists according to recognition results of the two recognition units. The limb identification module is responsible for identifying the postures of the head and the arms and judging the limb micro-motion category of the skeleton; the gesture recognition module is responsible for comparing the acquired gesture image information with a predefined gesture posture. By the monitoring method combining limb recognition and gesture recognition, the most accurate result can be pre-judged under the condition that the limb or gesture is shielded. The output result is sent to the control module, if the stealing behavior exists, the control module sends an instruction to the voice reminding module, and the voice reminding module sends a reminding sound (for example, a warning sound of 'careful property') so as to realize the recognition monitoring and reminding of the stealing behavior based on the micro-action of the limbs in the elevator cage.
Drawings
Fig. 1 is a schematic flow chart of a method for monitoring elevator car theft based on upper limb micro-action recognition according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an elevator car theft monitoring system based on upper limb micro-action recognition according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
As shown in fig. 1, an embodiment of the present invention provides a method for monitoring elevator car theft based on upper limb micro-motion recognition, including the following steps:
s101: obtaining passenger video stream information in an elevator car under a plurality of angles;
specifically, passenger video stream information in the elevator car can be acquired from a plurality of angles such as the top of the elevator car and the angles of the peripheral side walls, and multi-angle monitoring is achieved. When the occlusion condition exists, the clearest upper limb image information with least occlusion can be selected from the acquired video stream.
S102: framing the passenger video stream information, and performing image preprocessing on each frame of image;
specifically, the image preprocessing includes at least: the method specifically comprises the steps of determining a key threshold value of image binarization, segmenting an image background and an object through binarization, enhancing image contrast through gray level stretching, then eliminating image interference and noise, and combining a series of processing such as changing and correcting image inclination.
S103: performing head and arm posture recognition on the preprocessed image, and judging the type of the limb micro-motion; detecting whether predefined gesture postures exist in the image or not; judging whether suspected theft exists or not by combining the judgment result of the micro-action category of the limb and the detection result of the gesture;
specifically, limb micro-motion characteristic parameters and gesture posture characteristic parameters are extracted from the image, and an upper limb micro-motion vector is formed based on the extracted characteristic parameters;
for example, when performing posture recognition of the head and the arm, the extracted limb micro-motion characteristic parameters include: the swing amplitude of the head, the longitudinal extension amplitude of the arm and the transverse cutting amplitude of the arm. Correspondingly, the categories of limb micro-movements mainly include the following categories: the movement of the head for line-of-sight tracking, the movement of arm swing, the swing width of the forearm in the special limb movement, and the limb movement of the hand.
For example, when performing gesture detection, the extracted gesture feature parameters include: a rectangle width to height ratio, a shape ratio, a perimeter of the gesture, and a gesture area of the gesture periphery.
And comparing the similarity of the upper limb micro-motion vector with the upper limb micro-motion vector in the stealing template library, and taking the gesture category corresponding to the upper limb micro-motion vector in the stealing module with the highest similarity as the detection result of the gesture posture.
Specifically, because of the existence of shielding, whether possible stealing actions exist can not be well judged according to a certain action posture, and in order to overcome the shielding problem, the invention comprehensively judges whether suspected stealing actions exist by identifying the actions of the hand limbs and combining the micro action condition of the limbs, particularly the forearm.
S104: and if suspected theft exists, generating a voice reminding instruction so as to carry out voice reminding.
If the suspected theft exists, the steps S101 to S103 are repeated.
Example 2
As shown in fig. 2, an embodiment of the present invention provides an elevator car theft monitoring system based on upper limb micro-motion recognition, which includes an information acquisition module, an image preprocessing module, an upper limb micro-motion recognition module, a control module, and a voice prompt module;
the information acquisition module is used for acquiring passenger video stream information in the elevator car under a plurality of angles. And the image preprocessing module is used for framing the passenger video stream information and preprocessing images of each frame. The upper limb micro-motion recognition module is used for recognizing the postures of the head and the arms of the preprocessed image and judging the classes of the limb micro-motion; detecting whether a predefined gesture exists in the image; and judging whether suspected theft exists or not by combining the judgment result of the micro-action category of the limb and the detection result of the gesture. The control module is used for generating a voice alarm instruction and sending the voice alarm instruction to the voice reminding module for voice reminding when suspected theft exists.
Specifically, the information acquisition module comprises a plurality of image collectors; the image collectors are respectively arranged on the top of the elevator car and the peripheral side walls.
As an implementation manner, the upper limb fine motion recognition module comprises a limb recognition unit, a gesture recognition unit and a judgment unit; the limb identification unit is used for extracting limb micro-motion characteristic parameters from the image. The gesture recognition unit is used for extracting gesture attitude characteristic parameters from the image. The judgment unit is used for forming an upper limb micro-action vector according to the extracted parameters, comparing the similarity of the upper limb micro-action vector with the upper limb micro-action vector in the stealing template library, and taking the gesture category corresponding to the upper limb micro-action vector in the stealing module with the highest similarity as a detection result of the gesture posture, so that the most accurate result is pre-judged under the condition that an arm or a gesture is shielded.
Specifically, the process of constructing the stealing template library is as follows: and extracting corresponding characteristic parameters of known categories from the image by using an upper limb micro-motion recognition module and forming a vector so as to form a stealing template library.
In addition, the monitoring system also comprises a power supply module and a power supply detection module; and the power supply module is connected with other modules. The power supply detection module is used for detecting the electric quantity of the power supply module, and when the electric quantity is detected to be lower than the threshold electric quantity, an alarm is given out.
The elevator car stealing behavior monitoring method and system based on upper limb micro-motion recognition comprehensively utilize a target detection algorithm, an image processing technology and a computer vision library, and can effectively prevent elevator stealing events.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. The elevator car stealing behavior monitoring method based on upper limb micro-motion recognition is characterized by comprising the following steps of
Step 1: obtaining passenger video stream information in an elevator car under a plurality of angles;
step 2: framing the passenger video stream information, and performing image preprocessing on each frame of image;
and step 3: performing head and arm posture recognition on the preprocessed image, and judging the type of the limb micro-motion; detecting whether a predefined gesture exists in the image; judging whether suspected theft exists or not by combining the judgment result of the micro-action category of the limb and the detection result of the gesture;
and 4, step 4: and if suspected theft exists, generating a voice reminding instruction so as to carry out voice reminding.
2. The elevator car theft monitoring method based on upper limb fine motion recognition according to claim 1, wherein the image preprocessing at least comprises: graying, image smoothing, binarization and morphological processing.
3. The elevator car theft monitoring method based on upper limb fine movement recognition according to claim 1, wherein the step 3 specifically comprises:
extracting limb micro-motion characteristic parameters and gesture posture characteristic parameters from the image, and forming an upper limb micro-motion vector based on the extracted characteristic parameters;
and comparing the similarity of the upper limb micro-motion vector with the upper limb micro-motion vector in the stealing template library, and taking the gesture category corresponding to the upper limb micro-motion vector in the stealing module with the highest similarity as the detection result of the gesture posture.
4. The method for monitoring the stealing behavior of the elevator car based on the micro-motion recognition of the upper limb according to claim 3, wherein in the step 3, when the posture of the head and the arm is recognized, the extracted micro-motion characteristic parameters of the limb comprise: the swing amplitude of the head, the longitudinal extension amplitude of the arm and the transverse cutting amplitude of the arm.
5. The elevator car theft monitoring method based on upper limb micro-motion recognition according to claim 3, wherein in the step 3, when the gesture posture is detected, the extracted gesture posture characteristic parameters comprise: a rectangle width to height ratio of the gesture periphery, a shape ratio, a perimeter of the gesture, and a gesture area.
6. Elevator car monitoring system that takes action of stealing based on upper limbs fine motion is discerned, its characterized in that includes:
the information acquisition module is used for acquiring passenger video stream information in the elevator car under a plurality of angles;
the image preprocessing module is used for framing the passenger video stream information and preprocessing images of each frame;
the upper limb micro-motion recognition module is used for recognizing the postures of the head and the arms of the preprocessed image and judging the types of the micro-motion of the limbs; detecting whether a predefined gesture exists in the image; judging whether suspected theft exists or not by combining the judgment result of the micro-action category of the limb and the detection result of the gesture;
and the control module is used for generating a voice alarm instruction and sending the voice alarm instruction to the voice reminding module for voice reminding when suspected theft exists.
7. The elevator car theft monitoring system based on upper limb fine motion recognition according to claim 6, wherein the information acquisition module comprises a plurality of image collectors; a plurality of the image collector sets up respectively on elevator car top and lateral wall all around.
8. The elevator car theft monitoring system based on upper limb fine motion recognition as claimed in claim 6, wherein the upper limb fine motion recognition module comprises a limb recognition unit, a gesture recognition unit and a judgment unit;
the limb identification unit is used for extracting limb micro-motion characteristic parameters from the image;
the gesture recognition unit is used for extracting gesture feature parameters from the image;
and the judging unit is used for forming an upper limb micro-motion vector according to the extracted parameters, comparing the similarity of the upper limb micro-motion vector with the upper limb micro-motion vector in the stealing template library, and taking the gesture category corresponding to the upper limb micro-motion vector in the stealing module with the highest similarity as the detection result of the gesture posture.
9. The elevator car theft monitoring system based on upper limb fine motion recognition according to claim 6, further comprising a power module; and the power supply module is connected with other modules.
10. The elevator car theft monitoring system based on upper limb micro-action recognition according to claim 9, further comprising a power detection module for detecting the power of the power module and issuing an alarm when the detected power is lower than a threshold power.
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CN112149576A (en) * 2020-09-24 2020-12-29 杭州宣迅电子科技有限公司 Elevator safety real-time monitoring management system based on image analysis
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120127306A1 (en) * 2010-11-19 2012-05-24 Honeywell International Inc. Security video detection of personal distress and gesture commands
CN102881100A (en) * 2012-08-24 2013-01-16 济南纳维信息技术有限公司 Video-analysis-based antitheft monitoring method for physical store
CN105518755A (en) * 2013-09-06 2016-04-20 日本电气株式会社 Security system, security method, and non-temporary computer-readable medium
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