Segmenting, modeling, and matching video clips containing multiple moving objects

Authors:
Fred Rothganger;Svetlana Lazebnik;Cordelia Schmid;Jean Ponce
Affiliations:
Department of Computer Science and Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL;Department of Computer Science and Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL;INRIA Rhône-Alpes, Montbonnot, France;Department of Computer Science and Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL
Venue:
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Year:
2004

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Abstract

This paper presents a novel representation for dynamic scenes composed of multiple rigid objects that may undergo different motions and be observed by a moving camera. Multi-view constraints associated with groups of affine-invariant scene patches and a normalized description of their appearance are used to segment a scene into its rigid parts, construct three-dimensional projective, affine, and Euclidean models of these parts, and match instances of models recovered from different image sequences. The proposed approach has been implemented, and it is applied to the detection and recognition of moving objects in video sequences and the identification of shots that depict the same scene in a video clip (shot matching).