The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
A region-level graph labeling approach to motion-based segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Object segmentation in videos from moving camera with MRFs on color and motion features
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Simultaneous motion estimation and segmentation
IEEE Transactions on Image Processing
Unsupervised video segmentation based on watersheds and temporal tracking
IEEE Transactions on Circuits and Systems for Video Technology
Semiautomatic segmentation and tracking of semantic video objects
IEEE Transactions on Circuits and Systems for Video Technology
Automatic segmentation of moving objects in video sequences: a region labeling approach
IEEE Transactions on Circuits and Systems for Video Technology
Semiautomatic video object segmentation using VSnakes
IEEE Transactions on Circuits and Systems for Video Technology
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This paper presents a novel block-based moving region detection algorithm to segment objects. The frame is first partitioned into homogeneous regions. Moving region is then determined by a voting procedure of pixels within the region. To exploit the local features, we divide the frame into n × n blocks and perform block analysis for moving object segmentation. An iterative motion re-estimation technique is developed to obtain reliable block motion parameters. The block eigen value is used to measure the block texture. Block location corresponding to the region partition is also considered as a clue. Based on motion, texture and location information, moving regions are classified. Experimental results show that our approach is robust and achieves remarkable performance.