2014
CVPR
CVPR 2014
T-Linkage: A Continuous Relaxation of J-Linkage for Multi-Model Fitting
Abstract
This paper presents an improvement of the J-linkage algorithm for fitting multiple instances of a model to noisy data corrupted by outliers. The binary preference analysis implemented by J-linkage is replaced by a continuous (soft, or fuzzy) generalization that proves to perform better than J-linkage on simulated data, and compares favorably with state of the art methods on public domain real datasets.
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Interdisciplinary Bridge
- Artificial Intelligence and Computer Vision and Mathematics & Optimization
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Trend Setter
- Robustness
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Hot Topic Early Bird
- robust estimation