Publication Type : Journal Article
Publisher : Springer US
Source : Applied Intelligence
Url : https://link.springer.com/article/10.1007/s10489-021-02636-4
Campus : Amritapuri
School : Department of Computer Science and Engineering, School of Computing
Center : Computer Vision and Robotics
Department : Computer Science
Year : 2021
Abstract : Video synopsis is an effective technique for the efficient analysis of long videos in a short time. To generate a compact video, multiple tracks of moving objects, which we call as tubes are displayed simultaneously by rearranging them along the time axis. Contemporaneous video synopsis approaches focus on collision avoidance, or preservation of chronological order among tubes. However, generation of an adaptive personalized user-oriented synopsis video congruent to users’ preferences has yet not been thoroughly experimented. This paper propounds a framework for personalized visualization of synopsis video, integrating pertinent object attributes such as color, type, size, speed, travel path and direction towards generation of synopsis video for precise inference of user needs. The framework motivates users to interactively define queries for creation of the targeted synopsis.
Cite this Research Publication : Namitha, K., Narayanan, A. & Geetha, M. Interactive visualization-based surveillance video synopsis. Appl Intell 52, 3954–3975 (2022)