Video object segmentation and tracking using region-based statistics

Block matching motion estimation plays significant role for video processing and Computer Vision. Various methods based on mean shift and particle trackers are used to track the object on video sequence. Block matching algorithm is normally used for video compression technique. A novel, simple and fast block matching algorithm has been proposed using predictive motion vector for object tracking. Color histogram is used for matching criteria for the motion tracking. The proposed algorithm is considered with a flexible size of block as well as pixel displacement. Also early termination of the object as well as object out of boundary is considered. Experiments were conducted on different types of real world movie sequences.

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Spatiotemporal Region Enhancement and Merging for Unsupervized Object Segmentation

Ryan¹,

Amer²,

Gagnon³

2009

EURASIP Journal on Image and Video Processing

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Video object segmentation and tracking using region-based statistics

Cited by 7 publications

References 29 publications

Automatic body segmentation with graph cut and self-adaptive initialization level set (SAILS)

Automatic body segmentation with graph cut and self-adaptive initialization level set (SAILS)

Novel block matching algorithm using predictive motion vector for video object tracking based on color histogram

Spatiotemporal Region Enhancement and Merging for Unsupervized Object Segmentation

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