Video structured description technology based intelligence analysis of surveillance videos for public security applications

摘要

Video surveillance is an integrated system with strong prevention capabilities and widely used in military, customs, police, fire fighting, airports, railways, urban transport and many other public places. It's an important part of security system because of its visualized, accurate, timely and rich information content. Video surveillance has become the main tool due to its rich, intuitive and accurate information. However, with the large-scale construction of video surveillance systems all over the world, problems such as "useful information and clues cannot be found immediately with video big data" decrease detecting efficiency during crime prediction and public security governance. The increasing need of video based applications issues the importance of parsing and organizing the content in videos. However, the accurate understanding and managing video contents at the semantic level is still insufficient. The semantic gap between low level features and high level semantics cannot be bridged by manual or semi-automatic methods. In this paper, a semantic based model named video structural description (VSD) for representing and organizing the content in videos is introduced firstly. Video structural description aims at parsing video content into the text information, which uses spatiotemporal segmentation, feature selection, object recognition, and semantic web technology. The applications of VSD technology on public security from surveillance videos are given. The intelligent analysis of person and vehicle from surveillance video based on VSD is presented. The cloud enhanced platform managing surveillance videos is also given. At last, applications using VSD are introduced.