CN104809787A - Intelligent passenger flow volume statistics device based on camera - Google Patents
Intelligent passenger flow volume statistics device based on camera Download PDFInfo
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- CN104809787A CN104809787A CN201510201221.XA CN201510201221A CN104809787A CN 104809787 A CN104809787 A CN 104809787A CN 201510201221 A CN201510201221 A CN 201510201221A CN 104809787 A CN104809787 A CN 104809787A
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Abstract
The invention provides an intelligent passenger flow volume statistics device based on a camera. The device comprises a network camera and a DSP processing chip connected with the network camera, wherein the DSP processing chip comprises a passenger flow volume statistics module; the passenger flow volume statistics module is used for coding and analyzing each pixel in each frame of image collected by the network camera through an isotope labelling method, the rate of pixel density to the whole imaging picture width is utilized to realize width measurement of objects counted as the number of people, and images conforming to human body laws are counted in a message manner, so that a passenger flow volume statistics result can be obtained. According to the device, the relatively accurate passenger flow volume statistics function is realized when only part of processor resources of one network camera is occupied, so that lots of costs and resources are saved.
Description
Technical field
The present invention relates to a kind of passenger flow volume statistical method, particularly relate to a kind of intelligent passenger volume statistic device based on camera.
Background technology
In today that commercial competition is day by day fierce, effective commercial management has become the key factor of trade marketing success or failure.Business model progressively by traditional tradesman to the transformation of doing business having initiative, requirements at the higher level are proposed to commercial management person: within the shortest time, rapid reaction must be made to the faint change in market, and possess market foresight and save business operation cost to greatest extent, improve the rationality etc. of the science of market day-to-day operations decision-making, shopping environment comfortableness, deployment of human resources.The maximum leader of market discipline is commodity purchaser---client, how science, effectively time, analysis are spatially carried out to the volume of the flow of passengers, and make business decision timely fast, become the key of business, the success or not of retail trade marketing model.By to the quantitative statistics of Different periods passenger flow, make managerial personnel can increase staff in phase commuter rush hour, improve service quality, and then increase sale; Reduce a staff at one's leisure, avoid occurring that personnel waste.By continuous passenger flow statistics every day, one day, one week, the passenger flow Changing Pattern in January, a year can be drawn, managerial personnel accurately can be planned future activity, determine time, manpower and stock's size of order etc.Visible, a good passenger flow volume statistical system, very large effect can be played in a lot of business and Public Service Field, auxiliary administrator carries out decision-making, but the passenger flow volume statistical system in correlation technique all needs to be based upon huge resource (to be mainly reflected in the special server of needs to operate analysis, and the collection that the database of specialty carries out data arranges) on the basis that supports, concerning some small users and mechanism, the high cost paid for this reason, limits the demand of people to guest flow statistics.
Summary of the invention
To achieve these goals, an object of the present invention is to provide a kind of intelligent passenger volume statistic device based on camera, to solve the problem.
The invention provides a kind of intelligent passenger volume statistic device based on camera, the DSP process chip comprising IP Camera and be connected with this IP Camera, DSP process chip comprises guest flow statistics module; This guest flow statistics module is encoded for utilizing isotope-labeled method to each pixel in each two field picture of the video image that described IP Camera gathers and analyzes, with picture element density and overall imaging picture width for ratio, width measure is carried out to the object being calculated as the number of people, the image meeting human body rule is counted in the mode of message, obtains guest flow statistics result.
Further, this DSP process chip also comprises statistics output module, and statistics output module is used for exporting the guest flow statistics result of acquisition to terminal device.
Further, this IP Camera to be installed on directly over gateway and range of exposures is the crown of discrepancy personnel.
Compared with prior art the invention has the beneficial effects as follows: the segment processor resource only needing to take an IP Camera, both can complete relatively accurately guest flow statistics function, and save a large amount of costs and resource.
Accompanying drawing explanation
Fig. 1 is the structural representation of a kind of intelligent passenger volume statistic device based on camera of the present invention.
Embodiment
Also by reference to the accompanying drawings the present invention is described in further detail below by specific embodiment.
Shown in ginseng Fig. 1, Fig. 1 is the structural representation of a kind of intelligent passenger volume statistic device based on camera of the present invention.
Present embodiments provide a kind of intelligent passenger volume statistic device based on camera, comprising:
IP Camera 10 and DSP process chip 20, the DSP process chip 20 be connected with this IP Camera comprise guest flow statistics module 21; This guest flow statistics module 21 is encoded for utilizing isotope-labeled method to each pixel in each two field picture of the video image that described IP Camera gathers and analyzes, with picture element density and overall imaging picture width for ratio, width measure is carried out to the object being calculated as the number of people, the image meeting human body rule is counted in the mode of message, obtains guest flow statistics result.
The video image that this device collects with IP Camera is data basis, to form each frame picture of video image as analytic target, by identifying the contrast of concrete personage and background frame in object, carry out the counting of passenger flow, and carry out concentrating statistics, storing and analyze to these data.The method has merged the technology in multiple fields such as Video processing, image procossing, pattern-recognition and artificial intelligence, by isotope-labeled method, encodes to each pixel in each two field picture and analyzes, to reach the most accurate analytic statistics effect.This device adopts " grappling fixture " to calculate with " shoulder breadth " technical method combined, and decreases the impact because of factors such as hair color, intensity of illumination and shades.In the statistical basis that head color and background ground color are distinguished, add shoulder breadth statistics key element, with picture element density and overall imaging picture width for ratio, by camera DSP process chip, width measure is carried out to the object being calculated as " number of people " in real screen, the carrying out meeting human body rule counts, and considerably increases the accuracy rate of passenger flow statistics.This device counts in the mode of message, each data by one independently message add up, this message contains various information and key element, mainly comprises following several:
Implementor name, shooting first place;
Passenger flow title, state;
Time;
Counting notification;
Count report;
Real-time track;
With the sectional drawing of track;
Video clipping;
RTSP/RTP real time flow medium.
The passenger volume statistic device that the present embodiment provides, take resource few, only need the segment processor resource taking an IP Camera, both can complete relatively accurately guest flow statistics function, do not need huge server colony to realize, save a large amount of costs and resource.Meanwhile, applicability is strong, without forcing hardware requirement, can be suitable for most camera brand and type in the market, as long as camera has possessed the most basic data processing resources and ability.
In the present embodiment, this DSP process chip 20 also comprises statistics output module 22, and statistics output module 22 is for exporting the guest flow statistics result of acquisition to terminal device.This device can also generate a series of data analysis form automatically, except exporting except the numeric results of guest flow statistics by camera, can also be generated some according to time, region or other standards and arrange patterned statistical report form, help user very to get information about result.After this device is started working, statistics will real-time storage in camera, if user needs to check this result and analyze, then can by the statistical conversion software of networking with this camera, data and analysis result are derived, by computer interface, see statistical report form and real data intuitively.
In the present embodiment, this IP Camera 10 to be installed on directly over gateway and range of exposures is the crown of discrepancy personnel.When the IP Camera being provided with this device is deployed in gateway, its position of installing be in directly over gateway, height approximately is overhead about 2.5 meters, this highly also depends on the height of actual gateway and the horizontal extent of required detecting, gateway refers to general gateway, public place herein, under 2.5 meters of prerequisites of highly installing, the irradiating angle of camera should become complete vertical relation with place, ground platform, and what namely camera irradiated is the crown passing in and out this area people.Meanwhile, when these height installation and deployment, the horizontal extent that separate unit camera can be added up, between 2.5-3 rice, if there is the statistical demand exceeding this scope, then needs to install extra camera additional to add up.
The present invention contains the exact algorithm of double technique standard, encapsulate the output performance of the bearing message structure of this algorithm and the actuating medium of function and guest flow statistics result, the exact algorithm of double technique standard, have employed the interactive verification technique system that " grappling fixture " algorithm combines with " shoulder breadth " algorithm, for promoting the accurate rate of the method in guest flow statistics, encapsulate the message structure of this algorithm, have employed standardization, structurized message composition, every bar message is made up of fixed element and content, every element and content can be accurately positioned and identify, ageing and the accuracy in guest flow statistics process can be increased, the actuating medium of bearing message structure and function, the DSP process chip of mainstream network camera on market can be adopted, the generation of message and transmission rely on the processing capacity of general network camera, take relatively little resources of chip, ensure that this algorithm can be realized by the performance of camera completely, the output performance of guest flow statistics result, present for the computing machine of the final statistic analysis result of algorithm, graphical to final data, digitizing shows, user is enable to obtain statistics intuitively.
A series of detailed description listed is above only illustrating for feasibility embodiment of the present invention; they are also not used to limit the scope of the invention, all do not depart from the skill of the present invention equivalent implementations done of spirit or change all should be included within protection scope of the present invention.
To those skilled in the art, obviously the invention is not restricted to the details of above-mentioned one exemplary embodiment, and when not deviating from spirit of the present invention or essential characteristic, the present invention can be realized in other specific forms.Therefore, no matter from which point, all should embodiment be regarded as exemplary, and be nonrestrictive, scope of the present invention is limited by claims instead of above-mentioned explanation, and all changes be therefore intended in the implication of the equivalency by dropping on claim and scope are included in the present invention.
Claims (3)
1. based on an intelligent passenger volume statistic device for camera, it is characterized in that, comprising: IP Camera and the DSP process chip be connected with described IP Camera, described DSP process chip comprises guest flow statistics module;
Described guest flow statistics module is encoded for utilizing isotope-labeled method to each pixel in each two field picture of the video image that described IP Camera gathers and analyzes, with picture element density and overall imaging picture width for ratio, width measure is carried out to the object being calculated as the number of people, the image meeting human body rule is counted in the mode of message, obtains guest flow statistics result.
2. a kind of intelligent passenger volume statistic device based on camera according to claim 1, it is characterized in that, described DSP process chip also comprises statistics output module, and described statistics output module is used for exporting the guest flow statistics result of acquisition to terminal device.
3. a kind of intelligent passenger volume statistic device based on camera according to claim 1, is characterized in that, described IP Camera is installed on directly over gateway and range of exposures is the crown of discrepancy personnel.
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| CN201510201221.XA CN104809787B (en) | 2015-04-23 | 2015-04-23 | A kind of intelligent passenger volume statistic device based on camera |
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| CN201510201221.XA CN104809787B (en) | 2015-04-23 | 2015-04-23 | A kind of intelligent passenger volume statistic device based on camera |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2569924A (en) * | 2016-12-30 | 2019-07-03 | Du Yuchuan | Travel time distribution-based multimodal traffic anomaly detection method |
| CN117575684A (en) * | 2024-01-15 | 2024-02-20 | 杭州路过网络有限公司 | Passenger flow volume prediction method and system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7319776B2 (en) * | 2001-11-26 | 2008-01-15 | Fujitsu Limited | Image processing method and image processing program |
| CN101998115A (en) * | 2010-10-27 | 2011-03-30 | 江苏科技大学 | Embedded-type network camera with passenger flow counting function and passenger flow counting method |
| CN103345792A (en) * | 2013-07-04 | 2013-10-09 | 南京理工大学 | Sensor-depth-of-field-image-based passenger flow statistics device and method thereof |
| CN103839038A (en) * | 2012-11-23 | 2014-06-04 | 浙江大华技术股份有限公司 | People counting method and device |
| CN103871082A (en) * | 2014-03-31 | 2014-06-18 | 百年金海科技有限公司 | Method for counting people stream based on security and protection video image |
| CN104008396A (en) * | 2014-05-22 | 2014-08-27 | 南京邮电大学 | In and out people flow statistical method based on people head color and shape features |
-
2015
- 2015-04-23 CN CN201510201221.XA patent/CN104809787B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7319776B2 (en) * | 2001-11-26 | 2008-01-15 | Fujitsu Limited | Image processing method and image processing program |
| CN101998115A (en) * | 2010-10-27 | 2011-03-30 | 江苏科技大学 | Embedded-type network camera with passenger flow counting function and passenger flow counting method |
| CN103839038A (en) * | 2012-11-23 | 2014-06-04 | 浙江大华技术股份有限公司 | People counting method and device |
| CN103345792A (en) * | 2013-07-04 | 2013-10-09 | 南京理工大学 | Sensor-depth-of-field-image-based passenger flow statistics device and method thereof |
| CN103871082A (en) * | 2014-03-31 | 2014-06-18 | 百年金海科技有限公司 | Method for counting people stream based on security and protection video image |
| CN104008396A (en) * | 2014-05-22 | 2014-08-27 | 南京邮电大学 | In and out people flow statistical method based on people head color and shape features |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2569924A (en) * | 2016-12-30 | 2019-07-03 | Du Yuchuan | Travel time distribution-based multimodal traffic anomaly detection method |
| GB2569924B (en) * | 2016-12-30 | 2021-02-24 | Ogrands Innovation Inc | Travel time distribution-based multimodal traffic anomaly detection method |
| GB2587588A (en) * | 2016-12-30 | 2021-03-31 | Ogrands Innovation Inc | A method for detecting traffic anomaly with non-equidistant spatial-temporal division based on peak hour traffic flow rate |
| GB2588556A (en) * | 2016-12-30 | 2021-04-28 | Ogrands Innovation Inc | A method for detecting traffic anomaly based on travel time distribution with equidistant spatial-temporal division |
| GB2587588B (en) * | 2016-12-30 | 2021-10-27 | Touchless Innovation Ltd | A method for detecting traffic anomaly with non-equidistant spatial-temporal division based on peak hour traffic flow rate |
| GB2588556B (en) * | 2016-12-30 | 2021-10-27 | Touchless Innovation Ltd | A method for detecting traffic anomaly based on travel time distribution with equidistant spatial-temporal division |
| CN117575684A (en) * | 2024-01-15 | 2024-02-20 | 杭州路过网络有限公司 | Passenger flow volume prediction method and system |
| CN117575684B (en) * | 2024-01-15 | 2024-04-05 | 杭州路过网络有限公司 | Passenger flow volume prediction method and system |
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| CN104809787B (en) | 2017-11-17 |
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Address after: 100020 Beijing city Chaoyang District Guangshun North Street Hospital No. 33 Building 1 unit 7 room 808 Applicant after: Kean electric (Beijing) Polytron Technologies Inc Address before: 100020, 16B06, room 13, No. 2, Third Ring Road, East Third Ring Road, Beijing, Chaoyang District Applicant before: Kean electric (Beijing) system integration Co. Ltd. |
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Effective date of registration: 20180913 Address after: 100000 Chaoyang District, Beijing, Guangzhou, North 33 Avenue, 1 building, unit 7, 808 rooms. Co-patentee after: Shaanxi CLP Mdt InfoTech Ltd Patentee after: Kean electric Polytron Technologies Inc Address before: 100020 Chaoyang District, Beijing, Guangzhou, North 33 Avenue, 1 building, unit 7, 808 rooms. Patentee before: Kean electric (Beijing) Polytron Technologies Inc |
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