Multi-model Estimation in the Presence of Outliers
نویسندگان
چکیده
The estimation of models or structures from outlier-contaminated data containing multiple models has a large number of applications in computer vision, the study of the automated understanding of visual data: for instance, geometric figures may be detected from 2D points, and planar surfaces in a scene may be found in pairs of images of the scene using feature matches. This thesis describes a number of contemporary algorithms for multi-model estimation and some of their historical antecedents, as well as an evaluation methodology for the multi-model estimation problem.
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