A study on various methods used for video summarization and moving object detection for video surveillance applications

With the advancement in digital video technology, video surveillance has been playing its vital role for ensuring safety and security. The surveillance systems are deployed in wide range of applications to invigilate stuffs and to analyse the activities in the environment. From the single or multi surveillance camera, a huge amount of data is generated, stored and processed for security purpose. Due to time constraints, it is a very tedious process for an analyst to go through the full content. This limitation has been overcome by the use of video summarization. The video summarization is intended to afford comprehensible analysis of video by removing duplications and extracting key frames from the video. To make an easily interpreted outline, the various available video summarization methods will try to shot the summary of the main occurrences, scenes, or objects in a frame. Depending on the applications, it is required to summarize the happenings in the scene and detect the objects (static/dynamic) which is recorded in the video. Hence this paper provides the various methods used for video summarization and a comparative study of different techniques. It also presents different object detection, object classification and object tracking algorithms available in the literature.