Salient Points for Tracking Moving Objects in Video
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.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- US Department of Energy (US)
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 15011517
- Report Number(s):
- UCRL-CONF-208738; TRN: US200507%%499
- Resource Relation:
- Journal Volume: 5685; Conference: Presented at: Image and Video Communications and Processing, San Jose, CA (US), 01/17/2005--01/20/2005; Other Information: PBD: 20 Dec 2004
- Country of Publication:
- United States
- Language:
- English
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