A Model-Selection Framework for Multibody Structure-and-Motion of Image Sequences
International Journal of Computer Vision
Robust Algebraic Segmentation of Mixed Rigid-Body and Planar Motions from Two Views
International Journal of Computer Vision
Information fusion for multi-camera and multi-body structure and motion
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Nonparametric estimation of multiple structures with outliers
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Multi-body segmentation and motion number estimation via over-segmentation detection
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume part II
Perspective n-view multibody structure-and-motion through model selection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
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Multi-body structure-and-motion (MSaM) is the problem to establish the multiple-view geometry of several views of a 3D scene taken at different times, where the scene consists of multiple rigid objects moving relative to each other. We examine the case of two views. The setting is the following: given are a set of corresponding image points in two images, which originate from an unknown number of moving scene objects, each giving rise to a motion model. Furthermore, the measurement noise is unknown, and there are a number of gross errors, which are outliers to all models. The task to find an optimal set of motion models for the measurements is solved through Monte-Carlo sampling, careful statistical analysis of the data and simultaneous selection of multiple motion models.