Paper
27 April 2009 Summarization and visualization of target trajectories from massive video archives
Author Affiliations +
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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhanfeng Yue, Pramod Lakshmi Narasimha, and Pankaj Topiwala "Summarization and visualization of target trajectories from massive video archives", Proc. SPIE 7341, Visual Information Processing XVIII, 73410R (27 April 2009); https://doi.org/10.1117/12.818848
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KEYWORDS
Video

Visualization

Detection and tracking algorithms

Human-machine interfaces

Motion estimation

Particles

Fourier transforms

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