Parallel face recognition method with biological characteristics and local image characteristics

Abstract

The invention relates to a parallel face recognition method with biological characteristics and local image characteristics. The parallel face recognition method includes 1), importing video data; 2), judging whether a next frame image can be read or not, executing a step 3) if the next frame image can be read, executing a step 18) if the next frame image cannot be read; 3), transmitting data of the frame image into a video memory in a video card, and simultaneously, transmitting detection codes of a face into a processor of the video card; 4), detecting the face in the frame image in the video memory by the aid of the processor in the video card, judging whether the face is detected or not, executing a step 5) if the face is detected, and returning to the step 2) if the face is not detected; and 5), selecting the image of the detected face, marking the image as an F, initializing the number Mr of rough matching points and the number Me of fine matching points, namely Mr=0 and Me=0, and the like. Compared with the prior art, the parallel face recognition method has the advantages of wide application range, low realization cost, high recognition precision and the like.

Description

technical field [0001] The invention relates to a face recognition method, in particular to a parallel face recognition method combining biological features and local image features. Background technique [0002] Video analysis technology is a computer image visual analysis technology. By separating the background and the target in the scene, and then analyzing and tracking the target appearing in the surveillance video scene, it can partially replace manual staring at the screen or manual retrieval of video, and realize real-time or even High-speed retrieval is of great significance to promoting social stability and ensuring the safety of people's lives and properties. [0003] Face recognition technology is an important part of intelligent video analysis technology. It automatically detects and tracks faces in surveillance video images, and then performs a series of related technical processing on the detected faces, including face image acquisition, Face positioning, fac...

AI Technical Summary

Problems solved by technology

However, for the existing video surveillance system, hardware equipment needs to be added; the camera needs calibration and distortion correction, and once the position is moved, it needs to be re-calibrated, which must be implemented by professionals

3D image face recognition technology can solve the lighting problem to a certain extent, but its shortcomings are also obvious. First, the acquisition equipment is extremely complex and expensive; second, it cannot be compatible with existing visible light face image data, which greatly limits their applications. application, hindering the 3D image method from becoming the mainstream face recognition technology

The related system developed by Li Ziqing and others from the Institute of Automation of the Chinese Academy of Sciences was applied to identity verification at the Shanghai World Expo and achieved good results. The disadvantage is that it requires special infrared acquisition equipment, and the cost of rebuilding or rebuilding the existing video surveillance system is quite expensive. It is more difficult to popularize

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