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

Fred Rothganger·Svetlana Lazebnik·Cordelia Schmid·Jean Ponce
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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 are observed by a moving camera. Multiview constraints associated with groups of affine-covariant scene patches and a normalized description of their appearance are used to segment a scene into its rigid components, construct three-dimensional models of these components, and match instances of models recovered from different image sequences. The proposed approach has been applied to the detection and matching of moving objects in video sequences and to shot matching, i.e., the identification of shots that depict the same scene in a video clip.

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AlgorithmsArtificial IntelligenceComputer SimulationImage EnhancementImage Interpretation, Computer-AssistedInformation Storage and RetrievalModels, TheoreticalMotionMovementPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueVideo RecordingJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, Non-P.H.S.

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Fred Rothganger, Svetlana Lazebnik, Cordelia Schmid, Jean Ponce. 2007. Segmenting, modeling, and matching video clips containing multiple moving objects.. https://doi.org/10.1109/tpami.2007.57

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