Retrieval by local motion

Authors:
Berna Erol;Faouzi Kossentini
Affiliations:
Ricoh California Research Center, Menlo Park, CA;Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, British Columbia, Canada
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2003

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Abstract

Motion feature plays an important role in video retrieval. The current literature mostly addresses motion retrieval only by camera motion and global motion of individual video objects in a video scene. In this paper, we propose two new motion descriptors that capture the local motion of the video object within its bounding box. The proposed descriptors are rotation and scale invariant and based on the angular and circular area variances of the video object and the variances of the angular radial transform coefficients. Experiments show that ranking obtained by querying with our proposed descriptors closely match with the human ranking.