CN110164109A - A kind of pedestrian target tracking based on deep learning - Google Patents
A kind of pedestrian target tracking based on deep learning Download PDFInfo
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- CN110164109A CN110164109A CN201910312934.1A CN201910312934A CN110164109A CN 110164109 A CN110164109 A CN 110164109A CN 201910312934 A CN201910312934 A CN 201910312934A CN 110164109 A CN110164109 A CN 110164109A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V8/00—Prospecting or detecting by optical means
- G01V8/10—Detecting, e.g. by using light barriers
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- 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
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/103—Static body considered as a whole, e.g. static pedestrian or occupant recognition
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- 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
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
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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
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- G—PHYSICS
- G08—SIGNALLING
- G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
- G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
- G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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- Physics & Mathematics (AREA)
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- General Health & Medical Sciences (AREA)
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- General Life Sciences & Earth Sciences (AREA)
- Computer Networks & Wireless Communication (AREA)
- Alarm Systems (AREA)
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Abstract
The invention discloses a kind of pedestrian target tracking based on deep learning, is related to pedestrian target tracking technical field, and when being varied to solve people's complexion, system can not identify the problem of just re-establishing user folder, leading to information clutter.The following steps are included: step 1: the typing region is prohibited from entering the image information of personnel and the whole network wanted criminal；Step 2: infrared human body induction device detects whether that someone carries out region；Step 3: carrying out face acquisition with camera；Step 4: image is analyzed；Step 5: information is compared；Step 6: being matched with ordinary person has been stored, newest information is stored in corresponding folder；Step 7: when not comparing matching personnel, information new folder being stored；Step 8: being matched with the personnel of being prohibited from entering, broadcast voice reminder staff；Step 9: being matched with wanted criminal, broadcast voice reminder staff, sent positioning and video information is alarmed.
Description
Technical field
The present invention relates to pedestrian target tracking technical field, it is specially a kind of based on the pedestrian target of deep learning with
Track method.
Background technique
Pedestrian target tracking is suitable for preventing road monitoring system mostly at present, by pedestrian's form and Facial Features into
Row identification and captures and save, so that the state of pedestrian records in road pavement, convenient for cell progress security protection work, allows personnel
The Information Statistics of disengaging it is more intuitive.
But pedestrian target tracking on the market can only realize the progress that personnel are captured and passed in and out with information at present
Single stored, but monitoring system automatically updates personnel's form and appearance information, and after a period of time, people's complexion is become
When change, system, which can not identify, just re-establishes a user folder, leads to information clutter, is difficult to arrange, therefore market in urgent need
It is existing to help people to solve the problems, such as to develop a kind of pedestrian target tracking based on deep learning.
Summary of the invention
The purpose of the present invention is to provide a kind of pedestrian target tracking based on deep learning, to solve above-mentioned background
When existing people's complexion is varied in technology, system, which can not identify, just re-establishes a user folder, leads to information
In a jumble, it is difficult to the problem of arranging.
To achieve the above object, the invention provides the following technical scheme: a kind of pedestrian target tracking based on deep learning
Method, including control module, wireless data transmission module, face recognition module, camera, server, infrared human body induction device,
USB port, Beidou module and voice broadcast module；
Wherein, the control module carries out two-way electric connection by wireless data transmission module and server；
The control module carries out two-way electric connection by wireless data transmission module and public security alarm platform；
The control module and face recognition module carry out two-way electric connection；
The output end of the camera and the input terminal of control module are electrically connected；
The output end of the infrared human body induction device and the input terminal of control module are electrically connected；
The output end of the USB port and the input terminal of control module are electrically connected；
The output end of the control module and the input terminal of voice broadcast module are electrically connected；
The control module and the two-way electric connection of Beidou module.
Preferably, a kind of tracking, comprising the following steps:
Step 1: before use, the region can be prohibited from entering personnel and the whole network wanted criminal by USB port by staff
Image information classification be transferred to control module, control module is transferred to after receiving image information by wireless data transmission module
Server is stored；
Step 2: infrared human body induction device senses the special infrared of human-body emitting after someone enters inspection area
Line, infrared human body induction device sends signal to control module at this time；
Step 3: control module receives signal, control module finds that signal, camera adopt face to camera
Collect and is transferred to control module；
Step 4: control module analyzes the image transmitting received to face recognition module, face recognition module
Color special type, template characteristic, structure feature in image are extracted, useful information is extracted and transmits information to control module；
Step 5: control module extracts the personal information and biography with the information matches according to information by wireless data transmission module
It is defeated by face recognition module to be compared, face recognition module compares the information of acquisition and the information of storage；
Step 6: face recognition module sends signal, control to control module after with having stored ordinary person and comparing successfully
Molding block receives signal and the information of the newest acquisition of the personnel is transferred to server by wireless data transmission module, and server will most
Freshly harvested information is stored in the file of the personnel and saves；
Step 6: matching personnel ought not compared, face recognition module sends signal to control module, and control module receives
The information of the newest acquisition of the personnel is transferred to server by wireless data transmission module to signal, server will most freshly harvested letter
Breath new folder is saved.
Step 7: face recognition module is sent to control module to be believed after being prohibited from entering personnel with the region and comparing successfully
Number, control module receives signal control voice broadcast module and opens, and voice broadcast module starts to broadcast voice reminder work people
Member has personnel's invasion, handles as early as possible.
Step 8: face recognition module sends signal, control to control module after with the success of the whole network wanted criminal's information comparison
Molding block receives signal control voice broadcast module and opens, and voice broadcast module starts to broadcast voice reminder staff someone
Member's invasion, is handled as early as possible, while control module control Beidou module positions position, and control module is by location information and entirely
Net wanted criminal's video information is issued by wireless data transmission module alarms in public security alarm platform.
Preferably, the control module uses the control module of model STM32.
Preferably, the face recognition module uses the face recognition module of model an array of stars 1000.
Preferably, the infrared human body induction device uses the infrared human body induction device of model HC-SR501, described
Beidou module uses the Beidou module of model SKG09D.
Preferably, the wireless data transmission module uses the wireless data transmission module of model YJ-43L, the voice broadcast mould
Block uses the voice broadcast module of model FS-VMP-27.
Compared with prior art, the beneficial effects of the present invention are: should be led to based on the pedestrian target tracking of deep learning
It crosses and personnel's appearance is acquired, information progress color special type, template characteristic, the structure feature of acquisition are analyzed and compared
It is right, when appearance matching degree is higher, the newest form of pedestrian and complexion information are stored, realized to people's metamorphosis
It is updated, allows system to become more intelligent, efficient, allow information storage to become more orderly, when monitoring personnel being allowed to arrange information
It is more convenient, it improves work efficiency, while reducing the labor intensity of monitoring personnel, solves people's complexion and be varied
When, system, which can not identify, just re-establishes a user folder, leads to information clutter, is difficult to the problem of arranging, while to taboo
Only enter being compared for personnel and the whole network wanted criminal, greatly improves the quality of security, while can effectively guarantee public affairs
Peace supervises wanted criminal, and work is arrested in effective help public security.
Detailed description of the invention
Fig. 1 is a kind of schematic illustration of pedestrian target tracking based on deep learning of the invention.
Fig. 2 is a kind of flowage structure schematic diagram of pedestrian target tracking based on deep learning of the invention.
In figure: 1, control module；2, wireless data transmission module；3, face recognition module；4, camera；5, server；6, red
Outside line human inductor；7, USB port；8, Beidou module；9, voice broadcast module.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.
A kind of a kind of embodiment provided by the invention referring to FIG. 1-2: pedestrian target track side based on deep learning
Method, including control module 1, wireless data transmission module 2, face recognition module 3, camera 4, server 5, infrared human body induction device
6, USB port 7, Beidou module 8 and voice broadcast module 9；
Wherein, control module 1 carries out two-way electric connection by wireless data transmission module 2 and server 5；
Control module 1 carries out two-way electric connection by wireless data transmission module 2 and public security alarm platform；
Control module 1 and face recognition module 3 carry out two-way electric connection；
The output end of camera 4 and the input terminal of control module 1 are electrically connected；
The output end of infrared human body induction device 6 and the input terminal of control module 1 are electrically connected；
The output end of USB port 7 and the input terminal of control module 1 are electrically connected；
The output end of control module 1 and the input terminal of voice broadcast module 9 are electrically connected；
Control module 1 and the two-way electric connection of Beidou module 8.
Further, a kind of tracking, comprising the following steps:
Step 1: before use, staff the region can be prohibited from entering personnel by USB port 7 and the whole network is ordered to arrest
The image information classification of criminal is transferred to control module 1, and control module 1 passes through wireless data transmission module 2 after receiving image information
Server 5 is transferred to be stored；
Step 2: infrared human body induction device 6 senses the special infrared of human-body emitting after someone enters inspection area
Line, infrared human body induction device 6 sends signal to control module 1 at this time；
Step 3: control module 1 receives signal, control module 1 finds signal to camera 4, camera 4 to face into
Row acquires and is transferred to control module 1；
Step 4: control module 1 analyzes the image transmitting received to face recognition module 3, recognition of face mould
Block 3 extracts color special type, template characteristic, structure feature in image, extracts useful information and transmits information to control mould
Block 1；
Step 5: control module 1 is extracted with the personal information of the information matches simultaneously according to information by wireless data transmission module 2
It is transferred to face recognition module 3 to be compared, face recognition module 3 compares the information of acquisition and the information of storage；
Step 6: face recognition module 3 sends signal to control module 1 after with having stored ordinary person and comparing successfully,
Control module 1 receives signal and the information of the newest acquisition of the personnel is transferred to server 5 by wireless data transmission module 2, services
Most freshly harvested information is stored in the file of the personnel and saves by device 5；
Step 6: matching personnel ought not compared, face recognition module 3 sends signal, control module 1 to control module 1
It receives signal and the information of the newest acquisition of the personnel is transferred to server 5 by wireless data transmission module 2, server 5 will be newest
The information new folder of acquisition is saved.
Step 7: face recognition module 3 is sent to control module 1 after being prohibited from entering personnel with the region and comparing successfully
Signal, control module 1 receive signal control voice broadcast module 9 and open, and voice broadcast module 9 starts to broadcast voice reminder work
There is personnel's invasion as personnel, handles as early as possible.
Step 8: face recognition module 3 sends signal to control module 1 after with the success of the whole network wanted criminal's information comparison,
Control module 1 receives signal control voice broadcast module 9 and opens, and voice broadcast module 9 starts to broadcast voice reminder work people
Member has personnel's invasion, handles as early as possible, while control module 1 controls Beidou module 8 and positions to position, and control module 1 will determine
Position information and the whole network wanted criminal's video information are issued by wireless data transmission module 2 alarms in public security alarm platform.
Further, control module 1 uses the control module 1 of model STM32.
Further, face recognition module 3 uses the face recognition module 3 of model an array of stars 1000.
Further, infrared human body induction device 6 of the infrared human body induction device 6 using model HC-SR501, Beidou mould
Block 8 uses the Beidou module 8 of model SKG09D.
Further, wireless data transmission module 2 of the wireless data transmission module 2 using model YJ-43L, the use of voice broadcast module 9
The voice broadcast module 9 of model FS-VMP-27.
It is obvious to a person skilled in the art that invention is not limited to the details of the above exemplary embodiments, Er Qie
In the case where without departing substantially from spirit or essential attributes of the invention, the present invention can be realized in other specific forms.Therefore, no matter
From the point of view of which point, the present embodiments are to be considered as illustrative and not restrictive, and the scope of the present invention is by appended power
Benefit requires rather than above description limits, it is intended that all by what is fallen within the meaning and scope of the equivalent elements of the claims
Variation is included within the present invention.Any reference signs in the claims should not be construed as limiting the involved claims.
Claims (6)
1. a kind of pedestrian target tracking based on deep learning, it is characterised in that: including control module (1), wireless data sending
Module (2), face recognition module (3), camera (4), server (5), infrared human body induction device (6), USB port (7), north
Struggle against module (8) and voice broadcast module (9)；
Wherein, the control module (1) carries out two-way electric connection by wireless data transmission module (2) and server (5)；
The control module (1) carries out two-way electric connection by wireless data transmission module (2) and public security alarm platform；
The control module (1) and face recognition module (3) carry out two-way electric connection；
The output end of the camera (4) and the input terminal of control module (1) are electrically connected；
The output end of the infrared human body induction device (6) and the input terminal of control module (1) are electrically connected；
The output end of the USB port (7) and the input terminal of control module (1) are electrically connected；
The output end of the control module (1) and the input terminal of voice broadcast module (9) are electrically connected；
The control module (1) and Beidou module (8) two-way electric connection.
2. a kind of tracking according to claim 1, which comprises the following steps:
Step 1: before use, the region can be prohibited from entering personnel and the whole network wanted criminal by USB port (7) by staff
Image information classification be transferred to control module (1), control module (1) passes through wireless data transmission module after receiving image information
(2) server (5) is transferred to be stored；
Step 2: infrared human body induction device (6) senses the special infrared of human-body emitting after someone enters inspection area
Line, infrared human body induction device (6) sends signal to control module (1) at this time；
Step 3: control module (1) receives signal, control module (1) finds signal to camera (4), and camera (4) is to people
Face is acquired and is transferred to control module (1)；
Step 4: control module (1) analyzes the image transmitting received to face recognition module (3), recognition of face mould
Block (3) extracts color special type, template characteristic, structure feature in image, extracts useful information and transmits information to control
Module (1)；
Step 5: control module (1) is extracted with the personal information of the information matches simultaneously according to information by wireless data transmission module (2)
It is transferred to face recognition module (3) to be compared, face recognition module (3) compares the information of acquisition and the information of storage；
Step 6: face recognition module (3) sends signal to control module (1) after with having stored ordinary person and comparing successfully,
Control module (1) receives signal and the information of the newest acquisition of the personnel is transferred to server by wireless data transmission module (2)
(5), most freshly harvested information is stored in the file of the personnel and saves by server (5)；
Step 6: matching personnel ought not compared, face recognition module (3) sends signal, control module to control module (1)
(1) it receives signal and the information of the newest acquisition of the personnel is transferred to server (5), server by wireless data transmission module (2)
(5) most freshly harvested information new folder is saved.
Step 7: face recognition module (3) is sent to control module (1) after being prohibited from entering personnel with the region and comparing successfully
Signal, control module (1) receive signal control voice broadcast module (9) and open, and voice broadcast module (9) starts to broadcast voice
It reminds staff to have personnel's invasion, handles as early as possible.
Step 8: face recognition module (3) sends signal to control module (1) after with the success of the whole network wanted criminal's information comparison,
Control module (1) receives signal control voice broadcast module (9) and opens, and voice broadcast module (9) starts to broadcast voice reminder
Staff has personnel's invasion, handles as early as possible, while control module (1) control Beidou module (8) positions position, controls
Module (1) by location information and the whole network wanted criminal's video information by wireless data transmission module (2) issue public security alarm platform into
Row alarm.
3. a kind of pedestrian target tracking based on deep learning according to claim 1, which is characterized in that the control
Molding block (1) uses the control module (1) of model STM32.
4. a kind of pedestrian target tracking based on deep learning according to claim 1, which is characterized in that the people
Face identification module (3) uses the face recognition module (3) of model an array of stars 1000.
5. a kind of pedestrian target tracking based on deep learning according to claim 1, which is characterized in that described red
Outside line human inductor (6) uses the infrared human body induction device (6) of model HC-SR501, and the Beidou module (8) uses
The Beidou module (8) of model SKG09D.
6. a kind of pedestrian target tracking based on deep learning according to claim 1, which is characterized in that the nothing
Line number transmission module (2) uses the wireless data transmission module (2) of model YJ-43L, and the voice broadcast module (9) uses model
The voice broadcast module (9) of FS-VMP-27.
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| CN201910312934.1A CN110164109A (en) | 2019-04-18 | 2019-04-18 | A kind of pedestrian target tracking based on deep learning |
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| CN201910312934.1A CN110164109A (en) | 2019-04-18 | 2019-04-18 | A kind of pedestrian target tracking based on deep learning |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112822294A (en) * | 2021-03-03 | 2021-05-18 | 河南大华安防科技股份有限公司 | High-reliability intelligent security alarm information transmission device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150347820A1 (en) * | 2014-05-27 | 2015-12-03 | Beijing Kuangshi Technology Co., Ltd. | Learning Deep Face Representation |
| CN105574506A (en) * | 2015-12-16 | 2016-05-11 | 深圳市商汤科技有限公司 | Intelligent face tracking system and method based on depth learning and large-scale clustering |
| CN108052925A (en) * | 2017-12-28 | 2018-05-18 | 江西高创保安服务技术有限公司 | A kind of cell personnel archives intelligent management |
| CN109447048A (en) * | 2018-12-25 | 2019-03-08 | 苏州闪驰数控系统集成有限公司 | A kind of artificial intelligence early warning system |
| CN109614916A (en) * | 2018-12-06 | 2019-04-12 | 郑州铁路职业技术学院 | Station passenger status real time monitor early warning computer system based on recognition of face |
-
2019
- 2019-04-18 CN CN201910312934.1A patent/CN110164109A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150347820A1 (en) * | 2014-05-27 | 2015-12-03 | Beijing Kuangshi Technology Co., Ltd. | Learning Deep Face Representation |
| CN105574506A (en) * | 2015-12-16 | 2016-05-11 | 深圳市商汤科技有限公司 | Intelligent face tracking system and method based on depth learning and large-scale clustering |
| CN108052925A (en) * | 2017-12-28 | 2018-05-18 | 江西高创保安服务技术有限公司 | A kind of cell personnel archives intelligent management |
| CN109614916A (en) * | 2018-12-06 | 2019-04-12 | 郑州铁路职业技术学院 | Station passenger status real time monitor early warning computer system based on recognition of face |
| CN109447048A (en) * | 2018-12-25 | 2019-03-08 | 苏州闪驰数控系统集成有限公司 | A kind of artificial intelligence early warning system |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112822294A (en) * | 2021-03-03 | 2021-05-18 | 河南大华安防科技股份有限公司 | High-reliability intelligent security alarm information transmission device |
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