Summarization and visualization of target trajectories from massive video archives
Zhanfeng Yue, Pramod Lakshmi Narasimha, Pankaj Topiwala · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
Video, especially massive video archives, is by nature dense information medium. Compactly presenting the activities of targets of interest provides an efficient and cost saving way to analyze the content of the video. In this paper, we propose a video content analysis system to summarize and visualize the trajectories of targets from massive video archives. We first present an adaptive appearance-based algorithm to robustly track the targets in a particle filtering framework. It provides high performance while facilitating implementation of this algorithm in hardware with parallel processing. Phase correlation algorithm is used to estimate the motion of the observation platform which is then compensated in order to extract the independent trajectories of the targets. Based on the trajectory information, we develop the interface for browsing the videos which enables us to directly manipulate the video. The user could scroll over objects to view their trajectories. If interested, he/she could click on the object and drag it along the displayed path. The actual video will be played in synchronous to the mouse movement.