CN202443476U - Multiple camera human face recognition system - Google Patents
Multiple camera human face recognition system Download PDFInfo
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- CN202443476U CN202443476U CN2012200553913U CN201220055391U CN202443476U CN 202443476 U CN202443476 U CN 202443476U CN 2012200553913 U CN2012200553913 U CN 2012200553913U CN 201220055391 U CN201220055391 U CN 201220055391U CN 202443476 U CN202443476 U CN 202443476U
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Abstract
The utility model relates to a multiple camera human face recognition system which comprises a plurality of cameras, a human face recognition device and a display device. The plurality of cameras are used to collect video streams of human faces and each camera is installed on a human flow channel according to predetermined spacing distance. The human face recognition device is connected with the plurality of cameras, used to obtain the video stream of each camera, and selects the best human face image from the video streams. The display device is connected with the human face recognition device and used to output and display the best human face image recognized by the human face recognition device. The multiple camera human face recognition system achieves a multiple camera human face collection without perception and cooperation of objects and increases the odds of success of front human face collection for pose-varied human faces.
Description
Technical field
The utility model belongs to the face identification system field, particularly a kind of multimachine position face identification system.
Background technology
Now, face recognition technology is applied in the video safety defense monitoring system gradually, and it uses prerequisite is the collection of people's face; And collecting the application foundation that front face is a face recognition technology, people's attitude has very big randomness in reality, can also force by the attitude of acquisition target in occasions such as safety check, entry and exit; Yet in the public cultural facilities place; For example museum, the Art Museum, library etc. can't force spectators to cooperate and gather people's face information, and in the practical application of video safety defense monitoring system, implement hidden collection often; Though can make not perception of acquisition target; But also caused the uncontrollable problem of the attitude of acquisition target, in addition, owing to gather the influence of place complex environment; People's face acquisition system based on single video camera mostly exists the low problem of acquisition rate, and how being implemented under the complex environment the people's face exact acquisition that need not to cooperate by the acquisition target unaware is the present problem demanding prompt solution in computer image processing technology field.
The utility model content
The purpose of the utility model is to provide a kind of multimachine position face identification system, realizes the people's face multimachine position that need not to cooperate by the acquisition target unaware is gathered, and improves front face collection success ratio under the bigger situation of human face posture randomness.
For addressing the above problem, the utility model relates to a kind of multimachine position face identification system, comprising:
Be used to gather some video cameras of the video flowing of people's face, every video camera is installed on people's circulation road by the predetermined interval distance;
Be connected and from the video flowing of gathering, select the face identification device of beautiful woman's face picture with said video camera;
Link to each other with said face identification device and export the display device that shows said beautiful woman's face picture.
Further, said video camera is three.
Further, the predetermined interval distance is 2 to 5 meters between the said video camera.
Further, the left rotation and right rotation angle of said video camera is respectively 20 degree, and the anglec of rotation is respectively 15 degree up and down.
Further, the setting height(from bottom) of said video camera is in 2 meters.
Further, said face identification device comprises:
Be connected with said video camera and with the recognition of face equipment of the video flowing reduction framing picture of gathering;
Be connected and store the memory device of said frame picture with said recognition of face equipment;
Be connected with said memory device and the front face picture from said frame picture in choose beautiful woman's face picture attitude differentiate compare facilities.
Further, said recognition of face equipment is the TMSDM6437 dsp processor.
Further, said memory device is EPROM.
Further, said attitude differentiation compare facilities is a Dragonball MX1 chip.
Compared with prior art; Some video cameras of the video flowing of the utility model through being provided for gathering people's face, every video camera is installed on people's circulation road by the predetermined interval distance, and setting is connected with said video camera; Be used to obtain the video flowing of every video camera; And from video flowing, choose the face identification device of beautiful woman's face picture, and be provided with in addition with said face identification device and link to each other, be used for beautiful woman's face picture of said face identification device identification is exported the display device of demonstration; Realization is gathered the people's face multimachine position that need not to cooperate by the acquisition target unaware, improves front face collection success ratio under the bigger situation of human face posture randomness.
Description of drawings
Fig. 1 is the connection layout of the multimachine position face identification system of the utility model one embodiment;
Fig. 2 is the installation diagram of the video camera seat in the plane of one embodiment of the invention;
Fig. 3 is the face identification device structural map of one embodiment of the invention three;
Fig. 4 is the concrete structural map of the face identification device among Fig. 3 of the present invention.
Embodiment
Below in conjunction with the accompanying drawing among the utility model embodiment, the technical scheme among the utility model embodiment is carried out clear, intactly description, obviously, described embodiment only is the utility model part embodiment, rather than whole embodiment.Based on the embodiment in the utility model, those of ordinary skills are not making the every other embodiment that is obtained under the creative work prerequisite, all belong to the scope of the utility model protection.
Fig. 1 is the connection layout of the multimachine position face identification system of the utility model one embodiment.
Multimachine position face identification system as shown in Figure 1, that the utility model provides specifically comprises: some video cameras 1, face identification device 2 and display devices 3, wherein,
Said some shooting 1 machines are used to gather the video flowing of people's face, and every video camera 1 is installed on people's circulation road by the predetermined interval distance.
Said face identification device 2 is connected with said video camera 1, is used to obtain the video flowing of every video camera 1, and from video flowing, chooses beautiful woman's face picture.
Said display device 3 links to each other with said face identification device, is used for beautiful woman's face picture of said face identification device identification is exported demonstration, and said display device 3 can be PC.
Fig. 2 is the installation diagram of the video camera seat in the plane of one embodiment of the invention.
Further; As shown in Figure 2; Said video camera 1 is three, and predetermined interval between the said video camera 1 on people's circulation road 4 distance is 2 to 5 meters, and for example three digital cameras can be installed in three diverse locations of passage according to the stream of people's direction by the predetermined interval distance.
Further, the left rotation and right rotation angle of said video camera 1 is respectively 20 degree, and the anglec of rotation up and down of said video camera 1 is respectively 15 degree; The selection of every video camera 1 seat in the plane needs according to current recognition of face characteristics, and promptly can to discern the attitude scope be left rotation and right rotation [20 ° ,+20 °] to people from system face; [15 ° of last lower angles; + 15 °], setting height(from bottom) is controlled in the 2000mm, and the collecting efficiency of every digital camera was 25 frame/seconds.
Fig. 3 is the face identification device structural map of one embodiment of the invention.
Further, as shown in Figure 3, said face identification device 2 comprises: recognition of face equipment 21, memory device 22 and attitude are differentiated compare facilities 23, wherein,
Recognition of face equipment 21 is connected with said video camera 1, is used to obtain the video flowing of every video camera 1, and with said video flowing reduction framing picture.
Attitude is differentiated compare facilities 23 and is connected with said memory device 22, is used for obtaining the front face picture from the frame picture, and from said front face picture, chooses beautiful woman's face picture.
The face identification device basic functional principle is following: some the digital cameras 1 through on the continuous path obtain Video stream information; Recognition of face equipment 21 reduces framing picture and be stored into said memory device 22 with Video stream information then; Then attitude is differentiated in 23 pairs of memory devices 22 of compare facilities the frame picture and is carried out people's face and detect and select the front face picture, from said front face picture, chooses everyone beautiful woman's face picture and output again.
Fig. 4 is the concrete structural map of the face identification device among Fig. 3 of the present invention.
Further; As shown in Figure 4; Said recognition of face equipment 21 is TMSDM6437 DSP (TMS320DM6437) processor, and TMS320DM6437 is that TI company releases, is high-performance, exploitation, dominant frequency 600MHz, 32 processor familys that fixed DSP Leonardo da Vinci is technological of low-cost Video Applications specially, and TMSDM6437 DSP can obtain the video flowing of each digital camera output; Secondly video flowing is carried out the reduction of frame picture; Restore every video camera per second 25 frame pictures, in the frame picture, carry out people's face subsequently and detect, detect the people of point range intercepting according to pixels face picture and name behind people's face; Name needs sequence number, the acquisition time according to the Image Acquisition video camera, with the picture-storage that obtains in memory device 22 separately.
Further, as shown in Figure 4, said memory device 22 is EPROM.
Further, as shown in Figure 4, it is Dragonball MX1 chip that said attitude is differentiated compare facilities 23; Dragonball MX1 is a imperial pearl chip that Motorola releases; Be characterized in low-power consumption, low frequency, good stability; Dragonball MX1 can differentiate human face posture; From three EPROM 22, obtain with people's face picture constantly by the image file naming order, the people's face picture that gets access to is extracted eigenwert carry out the attitude differentiation relatively, the front face picture of selecting a best outputs on the PC with this picture characteristic of correspondence value coding.
In sum; Some video cameras of the video flowing of the utility model through being provided for gathering people's face, every video camera is installed on people's circulation road by the predetermined interval distance, and setting is connected with said video camera; Be used to obtain the video flowing of every video camera; And from video flowing, choose the face identification device of beautiful woman's face picture, and be provided with in addition with said face identification device and link to each other, be used for beautiful woman's face picture of said face identification device identification is exported the display device of demonstration; Realization is gathered the people's face multimachine position that need not to cooperate by the acquisition target unaware, improves front face collection success ratio under the bigger situation of human face posture randomness.
Obviously, those skilled in the art can carry out various changes and modification to utility model and not break away from the spirit and the scope of the utility model.Like this, if these of the utility model are revised and modification belongs within the scope of the utility model claim and equivalent technologies thereof, then the utility model also is intended to comprise these change and modification.
Claims (9)
1. a multimachine position face identification system is characterized in that, comprising:
Be used to gather some video cameras of the video flowing of people's face, every video camera is installed on people's circulation road by the predetermined interval distance;
Be connected and from the video flowing of gathering, select the face identification device of beautiful woman's face picture with said video camera;
Link to each other with said face identification device and export the display device that shows said beautiful woman's face picture.
2. multimachine as claimed in claim 1 position face identification system is characterized in that said video camera is three.
3. multimachine as claimed in claim 2 position face identification system is characterized in that, the predetermined interval distance is 2 to 5 meters between the said video camera.
4. multimachine as claimed in claim 3 position face identification system is characterized in that, the left rotation and right rotation angle of said video camera is respectively 20 degree, and the anglec of rotation is respectively 15 degree up and down.
5. multimachine as claimed in claim 3 position face identification system is characterized in that the setting height(from bottom) of said video camera is in 2 meters.
6. like each described multimachine position face identification system of claim 1 to 5, it is characterized in that said face identification device comprises:
Be connected with said video camera and with the recognition of face equipment of the video flowing reduction framing picture of gathering;
Be connected and store the memory device of said frame picture with said recognition of face equipment;
Be connected with said memory device and the front face picture from said frame picture in choose beautiful woman's face picture attitude differentiate compare facilities.
7. multimachine as claimed in claim 6 position face identification system is characterized in that said recognition of face equipment is the TMSDM6437 dsp processor.
8. multimachine as claimed in claim 7 position face identification system is characterized in that said memory device is EPROM.
9. multimachine as claimed in claim 8 position face identification system is characterized in that, it is Dragonball MX1 chip that said attitude is differentiated compare facilities.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2012200553913U CN202443476U (en) | 2012-02-20 | 2012-02-20 | Multiple camera human face recognition system |
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| CN2012200553913U CN202443476U (en) | 2012-02-20 | 2012-02-20 | Multiple camera human face recognition system |
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| CN202443476U true CN202443476U (en) | 2012-09-19 |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104751136A (en) * | 2015-03-11 | 2015-07-01 | 西安理工大学 | Face recognition based multi-camera video event retrospective trace method |
| CN105635696A (en) * | 2016-03-22 | 2016-06-01 | 南阳理工学院 | Statistical method and device |
| CN106101734A (en) * | 2016-06-15 | 2016-11-09 | 广州科技职业技术学院 | The net cast method for recording of interaction classroom and system |
| CN107563341A (en) * | 2017-09-15 | 2018-01-09 | 赵立峰 | A kind of face identification device and a kind of face identification system |
| CN107578024A (en) * | 2017-09-15 | 2018-01-12 | 赵立峰 | A kind of face identification system |
| CN107590488A (en) * | 2017-10-27 | 2018-01-16 | 广州市浩翔计算机科技有限公司 | The face identification system that a kind of split-type quickly identifies |
| CN109035299A (en) * | 2018-06-11 | 2018-12-18 | 平安科技（深圳）有限公司 | Method for tracking target, device, computer equipment and storage medium |
| JP2019146134A (en) * | 2018-02-23 | 2019-08-29 | 京セラドキュメントソリューションズ株式会社 | Electronic apparatus |
| CN113452903A (en) * | 2021-06-17 | 2021-09-28 | 浙江大华技术股份有限公司 | Snapshot equipment, snapshot method and main control chip |
-
2012
- 2012-02-20 CN CN2012200553913U patent/CN202443476U/en not_active Expired - Fee Related
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104751136B (en) * | 2015-03-11 | 2018-04-27 | 西安理工大学 | A kind of multi-camera video event back jump tracking method based on recognition of face |
| CN104751136A (en) * | 2015-03-11 | 2015-07-01 | 西安理工大学 | Face recognition based multi-camera video event retrospective trace method |
| CN105635696A (en) * | 2016-03-22 | 2016-06-01 | 南阳理工学院 | Statistical method and device |
| CN106101734A (en) * | 2016-06-15 | 2016-11-09 | 广州科技职业技术学院 | The net cast method for recording of interaction classroom and system |
| CN107563341A (en) * | 2017-09-15 | 2018-01-09 | 赵立峰 | A kind of face identification device and a kind of face identification system |
| CN107578024A (en) * | 2017-09-15 | 2018-01-12 | 赵立峰 | A kind of face identification system |
| CN107563341B (en) * | 2017-09-15 | 2023-03-24 | 威海元程信息科技有限公司 | Face recognition device and face recognition system |
| CN107590488A (en) * | 2017-10-27 | 2018-01-16 | 广州市浩翔计算机科技有限公司 | The face identification system that a kind of split-type quickly identifies |
| JP2019146134A (en) * | 2018-02-23 | 2019-08-29 | 京セラドキュメントソリューションズ株式会社 | Electronic apparatus |
| CN109035299A (en) * | 2018-06-11 | 2018-12-18 | 平安科技（深圳）有限公司 | Method for tracking target, device, computer equipment and storage medium |
| WO2019237516A1 (en) * | 2018-06-11 | 2019-12-19 | 平安科技（深圳）有限公司 | Target tracking method and apparatus, computer device, and storage medium |
| CN109035299B (en) * | 2018-06-11 | 2023-03-31 | 平安科技（深圳）有限公司 | Target tracking method and device, computer equipment and storage medium |
| CN113452903A (en) * | 2021-06-17 | 2021-09-28 | 浙江大华技术股份有限公司 | Snapshot equipment, snapshot method and main control chip |
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| C14 | Grant of patent or utility model | ||
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| TR01 | Transfer of patent right |
Effective date of registration: 20180411 Address after: No. 345, No. 19, fresh water road, Huangpu District, Shanghai, No. 19 Patentee after: Shanghai Zhongyuan Electron & Engineering Co.,Ltd. Address before: Room 202, Room 202, No. 22, Pudong New Area Yushan Road, Shanghai, Shanghai Patentee before: Hua Jiaobao |
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| TR01 | Transfer of patent right | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20120919 Termination date: 20210220 |
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| CF01 | Termination of patent right due to non-payment of annual fee |