Intelligent face tracking system and method based on depth learning and large-scale clustering

A large-scale cluster and deep learning technology, applied in the field of security monitoring, can solve problems such as increased false alarm rate and missed detection rate, increased chance of criminals evading inspection, and restrictions on the large-scale application of intelligent monitoring systems. Reliability and robustness, improved processing efficiency, good scalability effects

Active Publication Date: 2016-05-11
SHENZHEN SENSETIME TECH CO LTD
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Problems solved by technology

Furthermore, when the size of the database reaches a certain order of magnitude (such as a million), the false alarm rate and missed detection rate of the current face recognition system will increase significantly, r...

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  • Intelligent face tracking system and method based on depth learning and large-scale clustering
  • Intelligent face tracking system and method based on depth learning and large-scale clustering
  • Intelligent face tracking system and method based on depth learning and large-scale clustering

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Embodiment Construction

[0019] The following is attached Figure 1-3 Each embodiment of the present invention will be described in detail.

[0020] like figure 1 As shown, the intelligent face chasing system based on deep learning and large-scale clusters includes: video input unit 10, distribution server 20, face recognition server cluster 30, streaming media server 40, distributed file server 50, message center server 60 , database 70, Web front-end server 80 and front-end output 90.

[0021] The video input unit 10 mainly decodes, analyzes and processes the video streams collected by multiple network cameras, and transmits the processed video frames to the distribution server 20 .

[0022] In a preferred embodiment, the video input unit 10 further includes an image acquisition unit 11 , a video decoding unit 12 and an image preprocessing unit 13 .

[0023] Wherein, the image collection unit 11 collects encoded video stream signals from multiple network cameras, and inputs the signals to the vid...

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Abstract

The invention relates to an intelligent face tracking system and method based on depth learning and large-scale clustering. The system comprises a video input unit, a distribution server, a face identification server cluster, a streaming media server, a distributed file server, a message center server, a web front server and a client of a common operation system. According to the invention, by use of large-scale cluster servers, based on depth learning based face identification technology, a quite high identification rate can still be maintained under the condition of degraded image quality, and more important, a quite low false alarm rate and a quite low missed examination rate are maintained in a large-scale database, such that the reliability and the robustness of the intelligent tracking system can be ensured, and the intelligent tracking system based on face identification can be really applied to the field of safety protection.

Description

technical field [0001] The invention belongs to the field of security monitoring, and specifically relates to a face chasing system and method based on deep learning and large-scale clusters. Background technique [0002] With the rapid development of the economy and the acceleration of urban construction, the population in the city is dense, the floating population is increasing, and the social crime rate is increasing year by year, which has caused urban management issues such as transportation, social security, and key area prevention in urban construction. . Therefore, in recent years, in response to the high mobility of criminals, the complexity of the situation, and the difficulty in the deployment and control of key personnel, the face-based intelligent control and escape system has emerged as the times require. This type of system can be applied to the traditional video surveillance network, and does not require the cooperation of users, so the operation is highly c...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/161G06V10/95G06F18/22
Inventor 张伟陈朝军李庆林梁伯均苏哲昆张帅王晶黄展鹏刘祖希鲁洋吕亦琛张广程
Owner SHENZHEN SENSETIME TECH CO LTD
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