CN104469309A - Tunnel pedestrian intrusion detection device and method - Google Patents
Tunnel pedestrian intrusion detection device and method Download PDFInfo
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- CN104469309A CN104469309A CN201410757405.XA CN201410757405A CN104469309A CN 104469309 A CN104469309 A CN 104469309A CN 201410757405 A CN201410757405 A CN 201410757405A CN 104469309 A CN104469309 A CN 104469309A
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Abstract
The invention provides a tunnel pedestrian intrusion detection device and method. The tunnel pedestrian intrusion detection device comprises a video collecting unit, an intelligent detecting unit, a storing unit, a display unit and an alarm unit. The video collecting unit is connected with the intelligent detecting unit, the storing unit and display unit. Video images collected by the collecting unit are transmitted to the intelligent detecting unit. By means of background learning, foreground detecting, intrusion area setting and intrusion judging, the intelligent detecting unit obtains tunnel pedestrian intrusion information and gives an alarm. The display unit receives and displays video information of the collecting unit and displays alarm information. The storing unit receives the video information collected by the collecting unit and stores pedestrian intrusion images detected by the intelligent detecting unit. The alarm unit receives a signal of the intelligent detecting unit and gives an alarm. According to the device and the method, intelligence is high, pedestrians intruding into a tunnel can be detected in time, an alarm can be given, and traffic accidents are avoided.
Description
Technical field
The invention belongs to intelligent video analysis monitoring field, relate to the technology such as video analysis, pattern recognition, intelligent transportation, artificial intelligence.
Background technology
China's means of transportation are becoming better and approaching perfection day by day, and highway, railway, tunnel quantity are also continuing to increase, and simultaneously increasingly easily, traffic safety and management of traffic order improve also brings into schedule in traffic.In tunnel, light is poor, and car is more, but often having pedestrian to avoid detouring to take a shortcut, taking a risk to walk from tunnel, this is very large traffic safety hidden danger.At present, the quantity of traffic administration personnel can not catch up with the quantity of means of transportation, someone monitors in real time can not to reach each traffic section, and, if monitor staff continued observation video more than 22 minutes, so can omit the site activity of 95%, mean that monitoring probability is down to 0.2%, namely rely on human eye detection reliability lower, so in the urgent need to intelligent monitoring device, assist traffic administration personnel to carry out traffic monitoring and control, this will have huge social benefit and economic benefit.At present, also relevant smart machine detects tunnel scene pedestrian, assists transport personnel carry out tunnel safety management and process the situation that pedestrian swarms into tunnel in time.
Summary of the invention
For solving the problem, the object of the present invention is to provide tunnel pedestrian's invasion detecting device and method.
These apparatus and method have higher intelligent, can detect in time swarm into pedestrian in tunnel monitoring region and and alarm, the generation avoided traffic accident.This device degree of intelligence is high, and self-learning capability is strong, and testing result is reliable and stable.
The technical solution used in the present invention is: tunnel pedestrian's invasion detecting device and method comprise video acquisition unit, intelligent detection unit, memory cell, display unit, alarm unit.
Described video acquisition unit is connected with intelligent detection unit, display unit, memory cell; Intelligent detection unit is connected with video acquisition unit, display unit, memory cell, alarm unit; Video acquisition unit and display unit and memory cell carry out the transmission of real-time video information by fiber optic cables; Video acquisition unit and intelligent detection unit carry out transmission of video by netting twine; Intelligent detection unit and memory cell, display unit carry out Signal transmissions by fiber optic cables; Intelligent detection unit exports I/O signal to alarm unit.
Described video acquisition unit comprises color camera, infrared illumination lamp, video compression coding module.
Described intelligent detection unit comprises Background learning module, foreground detection module, invasion region setting module, invasion judge module and alarm module, picture compression coding module.
Described memory cell comprises original video module and invasion picture module.
Described display unit is video wall or large-screen, for showing real-time video and intrusion detection result.
Described alarm unit mainly alarm.
Described video acquisition unit gathers real-time scene video by color camera, and pass to intelligent detection unit, meanwhile, after the video of collection carries out compressed encoding by video compression coding module, by Optical Fiber Transmission to the original video module in memory cell, put on record for store video.Color camera in described video acquisition unit has day and night translation function, and day mode collects coloured image, when surrounding environment brightness is lower than a certain threshold value, opens drainage pattern at night, utilizes infrared illumination lamp to throw light on, and then gather image.
Described intelligent detection unit, by Background learning module, set up image background model, and along with scene, the change of light etc., intelligence is carried out study and is upgraded, then foreground detection module is carried out, namely to people emerging in scene or thing, carry out position and feature detection, and real time record upgrades foreground information, namely invasion region setting module sets the region that in tunnel, pedestrian may occur, by foreground information and invasion regional location and the comparison of the time of invasion, judge whether to belong to tunnel pedestrian's intrusion event, if belong to pedestrian's invasion, then output alarm signal is to alarm unit, simultaneously, locking pedestrian positional information, be transferred to display unit, and tunnel pedestrian's intrusion event picture is carried out through picture compression coding module the invasion picture module that is transferred to after compressed encoding in memory cell, so that follow-up verification.
Background learning module in described intelligent detection unit, by carrying out Gauss's modeling to the image collected, utilize the Y of image, U, V component sets up the model library of image, the present invention adopts 2*2 region modeling point, each modeling point comprises four Gauss models, Gauss model mainly comprises model gray scale, model variance, Model Weight, for the first two field picture, carry out model parameter initialization, for the image that subsequent transmission is come, mate with four Gauss models at corresponding pixel points place respectively, if coupling, then corresponding Gauss model weights increase, simultaneously and Gauss model is upgraded, if do not mate, then replace the minimum Gauss model of weight, when occurring that weights are greater than modeling threshold value in modeling point four Gauss models, current pixel point modeling success, the successful pixel number of modeling in statistics present image, when pixel modeling success count is greater than setting threshold, then start foreground detection, otherwise, proceed Background learning.
Foreground detection module in described intelligent detection unit, detect emerging people or thing in scene, Gauss's modeling is carried out to the image that transmission comes, each modeling point comprises a Gauss model, compares, the Gauss model of modeling point Gauss model with corresponding background modeling point place if do not mated, then continue to compare with modeling point four neighborhood Gauss model, if all do not mated, be then defined as foreground point, otherwise be background dot.Terminate if current frame image modeling point detects, then expansion process is carried out to foreground point, belong to the pixel of same prospect with UNICOM, simultaneously, prospect is marked, and calculates the filling rate of foreground blocks, area, center, depth-width ratio information, stored in prospect historical information.
Invade region setting module in described intelligent detection unit, refer to the region forbidding occurring pedestrian in setting tunnel, by setting four region lines along tunnel edge, delineation invasion region.
Invade judge module in described intelligent detection unit, refer to and invasion judgement is carried out to the prospect detected.Due to judgement is the pedestrian information of invading, pedestrian's judgement is carried out to prospect, namely pedestrian is determine whether by foreground area, filling rate, depth-width ratio information, filling rate is the ratio of foreground pixel point and the prospect frame comprising the whole pixel of current prospect, and depth-width ratio is the ratio of the height and the width when the prospect frame comprising the whole pixel of current prospect.In tunnel pedestrian's intrusion detection, video acquisition unit is just installed tunnel, according to pedestrian's distance, the foreground area detected varies in size, the foreground area utilizing distance to detect is different, the i.e. difference of the depth of field, image is divided, be divided into three regions, each region prospect setting area maximin, when only having pedestrian to meet area constraints and depth-width ratio in corresponding region, then judge that current prospect is as pedestrian, this avoid the interference of too small fruit stone etc. simultaneously, it also avoid the mistake identification of dilly, improve recognition accuracy.After pedestrian's judgement terminates, center according to prospect changes, matched jamming is carried out to effective foreground information that prospect is behaved, and be less than rate of change threshold value further by the area change of pedestrian's prospect, the change of prospect average gray value is less than threshold value and carries out same prospect judgement restriction, if same prospect becomes, the match is successful, with the average gray value of prospect in current foreground information real-time update prospect historical data base, filling rate, area, center, depth-width ratio information, the effective prospect disappeared in the visual field is removed, to the average gray value of emerging effective prospect, filling rate, area, center, depth-width ratio information is stored in prospect historical data base.
Alarm module in described intelligent detection unit, refers to when prospect pedestrian appears at protecting tunnel region, then sends I/O alarm signal, and meanwhile, alarm picture is stored into by picture compression coding module in the invasion picture module in memory cell.
In described intelligent detection unit, picture compression coding module is used for alarm picture compressed encoding, is convenient to store.
In described memory cell, original video module is used for the video information that the transmission of receiver, video collecting unit comes, and the tunnel pedestrian that invasion picture module reception intelligent detection unit detects invades result picture, for preserving and follow-up verification.
Described display unit is video wall or large-screen, and the real-time scene video of receiver, video collecting unit also shows, and is connected with intelligent detection unit simultaneously, shows Intelligent Measurement result, and shows tunnel pedestrian and invade information.
Described alarm unit receives the alarm signal that intelligent detection unit transmission comes, if there is tunnel pedestrian's intrusion event, then reports to the police, and assists traffic control personnel to process in time, avoids traffic accident occurs.
The invention has the beneficial effects as follows: the pedestrian that these apparatus and method can enter in Intelligent Measurement tunnel, and alarm, the generation avoided traffic accident, for maintaining traffic order, ensures that traffic safety has important meaning.Meanwhile, save the cost of manpower monitoring, accuracy of detection is high, and reliability is strong.This installation cost is low, installs simple and convenient; Detection algorithm strong robustness, degree of intelligence is high.
Accompanying drawing explanation
Accompanying drawing is used to provide a further understanding of the present invention, and forms a part for specification, is used from explanation the present invention, is not construed as limiting the invention with example one of the present invention.In the accompanying drawings:
Fig. 1 is structured flowchart of the present invention.
Fig. 2 is Background learning module frame chart of the present invention.
Fig. 3 is foreground detection module frame chart of the present invention.
Fig. 4 is that the present invention invades judge module block diagram.
Fig. 5 is alarm condition key diagram of the present invention.
Embodiment
Below in conjunction with instantiation, each detailed problem involved by technical solution of the present invention is described.Be to be noted that described example is only intended to be convenient to the understanding of the present invention, therefore do not limit protection scope of the present invention.
As shown in Figure 1, be structured flowchart of the present invention, tunnel pedestrian's invasion detecting device and method comprise video acquisition unit 1, intelligent detection unit 2, memory cell 5, display unit 3, alarm unit 4.
Described video acquisition unit 1 is connected with intelligent detection unit 2, display unit 3, memory cell 5; Intelligent detection unit 2 is connected with video acquisition unit 1, display unit 3, memory cell 5, alarm unit 4; Video acquisition unit 1 carries out the transmission of real-time video information with display unit 3 and memory cell 5 by fiber optic cables; Video acquisition unit 1 and intelligent detection unit 2 carry out transmission of video by netting twine; Intelligent detection unit 2 and memory cell 5, display unit 3 carry out Signal transmissions by fiber optic cables; Intelligent detection unit 2 exports I/O signal to alarm unit 4.
Described video acquisition unit 1 comprises color camera 11, infrared illumination lamp 12, video compression coding module 13.
Described intelligent detection unit 2 comprises Background learning module 21, foreground detection module 22, invasion region setting module 23, invasion judge module 24 and alarm module 25, picture compression coding module 26.
Described memory cell 5 comprises original video module 51 and invasion picture module 52.
Described display unit 3 is video wall or large-screen, for showing real-time video and intrusion detection result.
Described alarm unit 4 mainly alarm.
Described video acquisition unit 1 gathers real-time scene video by color camera 11, and pass to intelligent detection unit 2, simultaneously, after the video gathered carries out compressed encoding by video compression coding module 13, by Optical Fiber Transmission to the original video module 51 in memory cell 5, put on record for store video.Color camera 11 in described video acquisition unit 1 has day and night translation function, and day mode collects coloured image, when surrounding environment brightness is lower than a certain threshold value, opens drainage pattern at night, utilizes infrared illumination lamp 12 to throw light on, and then gather image.
Described intelligent detection unit 2, by Background learning module 21, set up image background model, and along with scene, the change of light etc., intelligence is carried out study and is upgraded, then foreground detection module 22 is carried out, namely to people emerging in scene or thing, carry out position and feature detection, and real time record upgrades foreground information, namely invasion region setting module 23 sets the region that in tunnel, pedestrian may occur, and then enter invasion judge module 24, by foreground information and invasion regional location and the comparison of the time of invasion, judge whether to belong to tunnel pedestrian's intrusion event, if belong to pedestrian's invasion, alarm module 25 exports I/O alarm signal to alarm unit 4, simultaneously, locking pedestrian positional information, be transferred to display unit 3, and the invasion picture module 52 tunnel pedestrian's intrusion event picture is transferred to after picture compression coding module 26 carries out compressed encoding in memory cell 5, so that follow-up verification.
As shown in Figure 2, Background learning module 21 in described intelligent detection unit 2, by carrying out Gauss's modeling to the image collected, utilize the Y of image, U, V component sets up the model library of image, the present invention adopts 2*2 region modeling point, each modeling point comprises four Gauss models, Gauss model mainly comprises model gray scale, model variance, Model Weight, for the first two field picture, carry out model parameter initialization, for the image that subsequent transmission is come, mate with four Gauss models at corresponding pixel points place respectively, if coupling, then corresponding Gauss model weights increase, simultaneously and Gauss model is upgraded, if do not mate, then replace the minimum Gauss model of weight, when occurring that weights are greater than modeling threshold value in modeling point four Gauss models, current pixel point modeling success, the successful pixel number of modeling in statistics present image, when pixel modeling success count is greater than setting threshold, then start foreground detection, otherwise, proceed Background learning, modeling threshold value generally gets 1/5 ~ 1/3 of modeling point sum.
As shown in Figure 3, foreground detection module 22 in described intelligent detection unit 2, be detect emerging people or thing in scene, carry out Gauss's modeling to the image that transmission comes, each modeling point comprises a Gauss model, the Gauss model of modeling point Gauss model with corresponding background modeling point place is compared, if do not mated, then continue to compare, if all do not mated with modeling point four neighborhood Gauss model, then be defined as foreground point, otherwise be background dot.Terminate if current frame image modeling point detects, then expansion process is carried out to foreground point, belong to the pixel of same prospect with UNICOM, simultaneously, prospect is marked, and calculates the filling rate of foreground blocks, area, center, depth-width ratio information, stored in prospect historical data base.
Invade region setting module 23 in described intelligent detection unit 2, refer to the region forbidding occurring pedestrian in setting tunnel, by setting four region lines along tunnel edge, delineation invasion region.
As shown in Figure 4, in described intelligent detection unit 2, invade judge module 24, refer to and invasion judgement is carried out to the prospect detected.Due to judgement is the pedestrian information of invading, pedestrian's judgement is carried out to prospect, namely pedestrian is determine whether by foreground area, filling rate, depth-width ratio information, filling rate is the ratio of foreground pixel point and the prospect frame comprising the whole pixel of current prospect, and depth-width ratio is the ratio of the height and the width when the prospect frame comprising the whole pixel of current prospect.In tunnel pedestrian's intrusion detection, video acquisition unit 1 is just installed tunnel, according to pedestrian's distance, the foreground area detected varies in size, the foreground area utilizing distance to detect is different, the i.e. difference of the depth of field, image is divided, be divided into three regions, each region prospect setting area maximin, when only having pedestrian to meet area constraints and depth-width ratio in corresponding region, then judge that current prospect is as pedestrian, this avoid the interference of too small fruit stone etc. simultaneously, it also avoid the mistake identification of dilly, improve recognition accuracy.After pedestrian's judgement terminates, center according to prospect changes, matched jamming is carried out to effective foreground information that prospect is behaved, and be less than rate of change threshold value further by the area change of pedestrian's prospect, the change of prospect average gray value is less than threshold value and carries out same prospect judgement restriction, if same prospect becomes, the match is successful, with the average gray value of prospect in current foreground information real-time update historical data base, filling rate, area, center, depth-width ratio information, the effective prospect disappeared in the visual field is removed, to the average gray value of emerging effective prospect, filling rate, area, center, depth-width ratio information is stored in prospect historical data base.
Alarm module 25 in described intelligent detection unit 2, refers to when prospect pedestrian appears at protecting tunnel region, then sends I/O alarm signal, and meanwhile, alarm picture to be stored in the invasion picture module in memory cell 5 52 by picture compression coding module 26.
In described intelligent detection unit 2, picture compression coding module 26 is for by alarm picture compressed encoding, is convenient to store.
In described memory cell 5, original video module 51 transmits for receiver, video collecting unit 1 the video information of coming, and the tunnel pedestrian that invasion picture module 52 receives intelligent detection unit 2 detection invades result picture, for preserving and follow-up verification.
Described display unit 3 is video wall or large-screen, and the real-time scene video of receiver, video collecting unit 1 also shows, and is connected with intelligent detection unit 2 simultaneously, display Intelligent Measurement result, and shows tunnel pedestrian and invade information.
Described alarm unit 4 receives intelligent detection unit 1 and transmits the alarm signal of coming, if there is tunnel pedestrian's intrusion event, then reports to the police, and assists traffic control personnel to process in time, avoids traffic accident occurs.
As shown in Figure 5, be tunnel intrusion alarm situation explanation.In figure, two vertical direction straight lines represent the invasion zone boundary set along tunnel; horizontal two straight lines represent the invasion zone boundary of setting; when pedestrian appears at protection zone A; intelligent detection unit 2 detects that pedestrian invades information and reports to the police; when pedestrian appears at protection zone B, do not report to the police.
Any those skilled in the art may utilize the technology contents of above-mentioned announcement to be changed or be modified as the Equivalent embodiments of equivalent variations.But everyly do not depart from technical solution of the present invention content, any simple modification, equivalent variations and the remodeling done above embodiment according to technical spirit of the present invention, still belong to the protection range of technical solution of the present invention.
Claims (5)
1. tunnel pedestrian invasion detecting device and method, is characterized in that: described tunnel pedestrian's invasion detecting device and method comprise video acquisition unit, intelligent detection unit, memory cell, display unit, alarm unit.
2. apparatus and method according to claim 1, is characterized in that: described tunnel pedestrian's invasion detecting device is connected with intelligent detection unit, display unit, memory cell with video acquisition unit in method; Intelligent detection unit is connected with video acquisition unit, display unit, memory cell, alarm unit; Video acquisition unit and display unit and memory cell carry out the transmission of real-time video information by fiber optic cables; Video acquisition unit and intelligent detection unit carry out transmission of video by netting twine; Intelligent detection unit and memory cell, display unit carry out Signal transmissions by fiber optic cables; Intelligent detection unit exports I/O signal to alarm unit.
3. apparatus and method according to claim 1, it is characterized in that: in described tunnel pedestrian's invasion detecting device and method, video acquisition unit gathers real-time scene video by color camera, and pass to intelligent detection unit, simultaneously, after the video gathered carries out compressed encoding by video compression coding module, by Optical Fiber Transmission to the original video module in memory cell, put on record for store video; Color camera in described video acquisition unit has day and night translation function, and day mode collects coloured image, when surrounding environment brightness is lower than a certain threshold value, opens drainage pattern at night, utilizes infrared illumination lamp to throw light on, and then gather image.
4. apparatus and method according to claim 1, is characterized in that: in described tunnel pedestrian's invasion detecting device and method, intelligent detection unit comprises Background learning module, foreground detection module, invades region setting module, invades judge module and alarm module, picture compression coding module.
5. apparatus and method according to claim 1, it is characterized in that: intelligent detection unit in described tunnel pedestrian's invasion detecting device and method, by Background learning module, set up image background model, and along with scene, the change of light etc., intelligence is carried out study and is upgraded, then foreground detection module is carried out, namely to people emerging in scene or thing, carry out position and feature detection, and real time record upgrades foreground information, namely invasion region setting module sets the region that in tunnel, pedestrian may occur, by foreground information and invasion regional location and the comparison of the time of invasion, judge whether to belong to tunnel pedestrian's intrusion event, if belong to pedestrian's invasion, then output alarm signal is to alarm unit, simultaneously, locking pedestrian positional information, be transferred to display unit, and tunnel pedestrian's intrusion event picture is carried out through picture compression coding module the invasion picture module that is transferred to after compressed encoding in memory cell, so that follow-up verification.
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| CN201410757405.XA CN104469309A (en) | 2014-12-12 | 2014-12-12 | Tunnel pedestrian intrusion detection device and method |
| CN201510595412.9A CN105100757B (en) | 2014-12-12 | 2015-09-18 | Detector with integral structure |
| CN201510597878.2A CN105096603B (en) | 2014-12-12 | 2015-09-18 | Round-the-clock detection device |
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| CN201510595412.9A Active CN105100757B (en) | 2014-12-12 | 2015-09-18 | Detector with integral structure |
| CN201510597878.2A Active CN105096603B (en) | 2014-12-12 | 2015-09-18 | Round-the-clock detection device |
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| CN201510595412.9A Active CN105100757B (en) | 2014-12-12 | 2015-09-18 | Detector with integral structure |
| CN201510597878.2A Active CN105096603B (en) | 2014-12-12 | 2015-09-18 | Round-the-clock detection device |
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| CN110427865B (en) * | 2019-07-29 | 2023-08-25 | 三峡大学 | Human behavior video feature picture extraction and reconstruction method for high-voltage forbidden region |
| CN111310733A (en) * | 2020-03-19 | 2020-06-19 | 成都云盯科技有限公司 | Method, device and equipment for detecting personnel entering and exiting based on monitoring video |
| CN111310733B (en) * | 2020-03-19 | 2023-08-22 | 成都云盯科技有限公司 | Personnel access detection method, device and equipment based on monitoring video |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105096603A (en) | 2015-11-25 |
| CN105100757B (en) | 2018-09-18 |
| CN105100757A (en) | 2015-11-25 |
| CN105096603B (en) | 2018-01-09 |
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Application publication date: 20150325 |