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Robust Global Motion Estimation Oriented to Video Object Segmentation

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3 Author(s)
Bin Qi ; Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, QC ; Ghazal, M. ; Amer, A.

Most global motion estimation (GME) methods are oriented to video coding while video object segmentation methods either assume no global motion (GM) or directly adopt a coding-oriented method to compensate for GM. This paper proposes a hierarchical differential GME method oriented to video object segmentation. A scheme which combines three-step search and motion parameters prediction is proposed for initial estimation to increase efficiency. A robust estimator that uses object information to reject outliers introduced by local motion is also proposed. For the first frame, when the object information is unavailable, a robust estimator is proposed which rejects outliers by examining their distribution in local neighborhoods of the error between the current and the motion-compensated previous frame. Subjective and objective results show that the proposed method is more robust, more oriented to video object segmentation, and faster than the referenced methods.

Published in:

Image Processing, IEEE Transactions on  (Volume:17 ,  Issue: 6 )