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Proceedings Paper

Salient points for tracking moving objects in video
Author(s): Chandrika Kamath; Abel Gezahegne; Shawn Newsam; George Marlon Roberts
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Paper Abstract

Detection and tracking of moving objects is important in the analysis of video data. One approach is to maintain a background model of the scene and subtract it from each frame to detect the moving objects which can then be tracked using Kalman or particle filters. In this paper, we consider simple techniques based on salient points to identify moving objects which are tracked using motion correspondence. We focus on video with a large field of view, such as a traffic intersection with several buildings nearby. Such scenes can contain several salient points, not all of which move between frames. Using public domain video and two types of salient points, we consider how to make these techniques computationally efficient for detection and tracking. Our early results indicate that salient regions obtained using the Lowe keypoints algorithm and the Scale-Saliency algorithm can be used successfully to track vehicles in moderate resolution video.

Paper Details

Date Published: 14 March 2005
PDF: 12 pages
Proc. SPIE 5685, Image and Video Communications and Processing 2005, (14 March 2005); doi: 10.1117/12.587323
Show Author Affiliations
Chandrika Kamath, Lawrence Livermore National Lab. (United States)
Abel Gezahegne, Lawrence Livermore National Lab. (United States)
Shawn Newsam, Lawrence Livermore National Lab. (United States)
George Marlon Roberts, Lawrence Livermore National Lab. (United States)


Published in SPIE Proceedings Vol. 5685:
Image and Video Communications and Processing 2005
Amir Said; John G. Apostolopoulos, Editor(s)

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