Paper
7 May 2003 Voting-based simultaneous tracking of multiple video objects
Author Affiliations +
Proceedings Volume 5022, Image and Video Communications and Processing 2003; (2003) https://doi.org/10.1117/12.476704
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States
Abstract
In the context of content-oriented applications such as video surveillance and video retrieval this paper proposes a stable object tracking method based on both object segmentation and motion estimation. The method focuses on the issues of speed of execution and reliability in the presence of noise, coding artifacts, shadows, occlusion, and object split. Objects are tracked based on the similarity of their features in successive images. This is done in three steps: object segmentation and motion estimation, object matching, and feature monitoring and correction. In the first step, objects are segmented and their spatial and temporal features are computed. In the second step, using a non-linear voting strategy, each object of the previous image is matched with an object of the current image creating a unique correspondence. In the third step, object segmentation errors, such as when objects occlude or split, are detected and corrected. These new data are then used to update the results of previous steps, i.e., object segmentation and motion estimation. The contributions in this paper are the multi-voting strategy and the monitoring and correction of segmentation errors. Extensive experiments on indoor and outdoor video shots containing over 6000 images, including images with multi-object occlusion, noise, and coding artifacts have demonstrated the reliability and real-time response of the proposed method.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Aishy Amer "Voting-based simultaneous tracking of multiple video objects", Proc. SPIE 5022, Image and Video Communications and Processing 2003, (7 May 2003); https://doi.org/10.1117/12.476704
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CITATIONS
Cited by 15 scholarly publications.
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KEYWORDS
Video surveillance

Image segmentation

Video

Motion estimation

Feature extraction

Reliability

Detection and tracking algorithms

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