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A Model-Selection Framework for Multibody Structure-and-Motion of Image Sequences

机译:图像序列多体结构和运动的模型选择框架

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摘要

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.
机译:给定由多个刚性移动对象组成的场景的图像序列,多体结构和运动(MSaM)是将图像特征轨迹分割为不同的刚性对象并计算每个对象的多视图几何的任务。我们提出了一种基于模型选择的多体结构和运动框架。在恢复和选择过程中,将生成一组冗余的假设场景运动。该运动候选者池的每个子集都被视为图像特征轨迹的可能解释,并且最可能的解释是通过模型选择来选择的。该框架是通用的,可以与任何参数相机模型一起使用,也可以与不同模型的组合一起使用。它可以处理随时间变化的对应关系集,并且对实际数量的异常值具有鲁棒性。该框架针对不同的相机和场景模型进行了演示。

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