Di Zhong, Shih-Fu Chang. Long-Term Moving Object Segmentation and Tracking Using Spatio-Temporal Consistency. In IEEE International Conference on Image Processing (ICIP), Athen, Greece, October 2001.
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The success of object-based media representation and description (e.g., MPEG-4 and 7) depends largely on effective object segmentation tools. In this paper, we expand our previous work on automatic video region tracking and develop a robust - moving objects detection system. In our system, we first utilize innovative methods of combining color and edge information in improving the object motion estimation results. Then we use the long-term spatio-temporal constraints to achieve reliable object tracking over long sequences. Our extensive experiments demonstrate excellent results in handling challenging cases in general domains (e.g., stock footage) including depth-varying multi-layer background and fast camera motion
@InProceedings{dvmmPub30,
Author = {Zhong, Di and Chang, Shih-Fu},
Title = {Long-Term Moving Object Segmentation and Tracking Using Spatio-Temporal Consistency},
BookTitle = {IEEE International Conference on Image Processing (ICIP)},
Address = {Athen, Greece},
Month = {October},
Year = {2001}
}
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