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Progressive-X: Efficient, Anytime, Multi-Model Fitting Algorithm
2019 IEEE/CVF International Conference on Computer Vision (ICCV)
The Progressive-X algorithm, Prog-X in short, is proposed for geometric multi-model fitting. The method interleaves sampling and consolidation of the current data interpretation via repetitive hypothesis proposal, fast rejection, and integration of the new hypothesis into the kept instance set by labeling energy minimization. Due to exploring the data progressively, the method has several beneficial properties compared with the state-of-the-art. First, a clear criterion, adopted from RANSAC,doi:10.1109/iccv.2019.00388 dblp:conf/iccv/BarathM19 fatcat:3exupkbyxjcthhelp3b63ewl4i