Design Of A Video Retrieval System Software Based On Face Index

With the development of multimedia technology, video surveillance has been widely used in security, industrial production and other fields.Video surveillance generates vast amounts of video data, which is very inefficient for the public security department to extract effective information. If video information is efficiently extracted from video surveillance, video playback monitoring work will be reduced for public security departments workers.The human face information is the most important part of video information. According to the demand of the public security department video retrieval, based on the analysis of the current development status of the video retrieval,the paper puts forward and implements design of a video retrieval system software based on face index. The paper main work is as follows:A software framework is designed for video retrieval system based on face information. The software system can play and playback h. 264 format video files, and automatically detect and recognize the faces that exist in the video, extract facial images in time sequence and display them on the screen. Users can browse the detected faces as well as the period of the face in the video. Selecting a time period can play back the time.The face detection and face recognition methods are realized. Video face detection and face recognition algorithms which have prominent effect are applied to the development of video retrieval system based on face information. Face detection uses the Haar-like as Ada Boost method of characteristics. The Paper analyzes the feasibility of this method through the development tools VC + + 6.0. Face recognition adopts the face recognition method based on adaptive LBP threshold. The method has high recognition rate than traditional LBP face recognition methods under the condition of uneven illumination. The paper analyzes the face image change after extracting the adaptive LBP threshold feature. Face recognition experiment is carried out using the method. Finally, face detection and face recognition algorithms are applied to the video retrieval system based on face index. Video retrieval system that has function of face detection and face recognition is achieved, and the performance of the system is analyzed.