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Type: Journal article
Title: A Model-selection Framework for Multibody Structure-and-Motion of Image Sequences
Author: Schindler, K.
Suter, D.
Wang, H.
Citation: International Journal of Computer Vision, 2008; 79(2):159-177
Publisher: Kluwer Academic Publ
Issue Date: 2008
ISSN: 0920-5691
Statement of
Konrad Schindler, David Suter and Hanzi Wang
Abstract: Given an image sequence of a scene consisting of multiple rigidly moving objects, multi-body structure-and-motion (MSaM) is the task to segment the image feature tracks into the different rigid objects and compute the multiple-view geometry of each object. We present a framework for multibody structure-and-motion based on model selection. In a recover-and-select procedure, a redundant set of hypothetical scene motions is generated. Each subset of this pool of motion candidates is regarded as a possible explanation of the image feature tracks, and the most likely explanation is selected with model selection. The framework is generic and can be used with any parametric camera model, or with a combination of different models. It can deal with sets of correspondences, which change over time, and it is robust to realistic amounts of outliers. The framework is demonstrated for different camera and scene models.
Keywords: Multibody structure-and-motion
3D motion segmentation
Model selection
DOI: 10.1007/s11263-007-0111-7
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Computer Science publications

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