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Image motion estimation by clustering
Author(s) -
Bandopadhay Amit,
Aloimonos John Yiannis
Publication year - 1990
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.1850020409
Subject(s) - artificial intelligence , motion estimation , computer vision , pattern recognition (psychology) , computer science , cluster analysis , motion vector , matching (statistics) , similarity (geometry) , feature vector , displacement (psychology) , filter (signal processing) , image (mathematics) , feature (linguistics) , mathematics , psychology , linguistics , statistics , philosophy , psychotherapist
Image motion is estimated by matching feature “interest” points in different frames of video image sequences. The matching is based on local similarity of the displacement vectors. Clustering in the displacement vector space is used to determine the set of plausible match vectors. Subsequently, a similarity‐based algorithm performs the actual matching. The feature points are computed using a multiple‐filter image decomposition operator. The algorithm has been tested on synthetic as well as real video images. The novelty of the approach is that it handles multiple motions and performs motion segmentation.