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Proceedings Paper

Summarization and visualization of target trajectories from massive video archives
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Paper Abstract

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.

Paper Details

Date Published: 27 April 2009
PDF: 14 pages
Proc. SPIE 7341, Visual Information Processing XVIII, 73410R (27 April 2009); doi: 10.1117/12.818848
Show Author Affiliations
Zhanfeng Yue, FastVDO LLC (United States)
Pramod Lakshmi Narasimha, FastVDO LLC (United States)
Pankaj Topiwala, FastVDO LLC (United States)

Published in SPIE Proceedings Vol. 7341:
Visual Information Processing XVIII
Zia-Ur Rahman; Stephen E. Reichenbach; Mark Allen Neifeld, Editor(s)

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