Image analysis – Image segmentation
Reexamination Certificate
2006-10-26
2008-10-21
Mehta, Bhavesh (Department: 2624)
Image analysis
Image segmentation
Reexamination Certificate
active
07440615
ABSTRACT:
A fully automatic, computationally efficient segmentation method of video employing sequential clustering of sparse image features. Both edge and corner features of a video scene are employed to capture an outline of foreground objects and the feature clustering is built on motion models which work on any type of object and moving/static camera in which two motion layers are assumed due to camera and/or foreground and the depth difference between the foreground and background. Sequential linear regression is applied to the sequences and the instantaneous replacements of image features in order to compute affine motion parameters for foreground and background layers and consider temporal smoothness simultaneously. The Foreground layer is then extracted based upon sparse feature clustering which is time efficient and refined incrementally using Kalman filtering.
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Gong Yihong
Han Mei
Xu Wei
Akhavannik Hadi
Brosemer, Kolefas & Associates LLC
Mehta Bhavesh
NEC Laboratories America, Inc.
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