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GMS: Grid-Based Motion Statistics for Fast, Ultra-Robust Feature Correspondence
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Incorporating smoothness constraints into feature matching is known to enable ultra-robust matching. However, such formulations are both complex and slow, making them unsuitable for video applications. This paper proposes GMS (Grid-based Motion Statistics), a simple means of encapsulating motion smoothness as the statistical likelihood of a certain number of matches in a region. GMS enables translation of high match numbers into high match quality. This provides a real-time, ultra-robust
doi:10.1109/cvpr.2017.302
dblp:conf/cvpr/BianLMYNC17
fatcat:o4ton7rajra65nmgulku7db7q4