Probabilistic tensor voting for robust perceptual grouping

  title={Probabilistic tensor voting for robust perceptual grouping},
  author={Dian Gong and G{\'e}rard G. Medioni},
  journal={2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops},
We address the problem of unsupervised segmentation and grouping in 2D and 3D space, where samples are corrupted by noise, and in the presence of outliers. The problem has attracted attention in previous research work, but non-parametric outlier filtering and inlier denoising are still challenging. Tensor voting is a non-parametric algorithm that can infer local data geometric structure. Standard tensor voting considers outlier noise explicitly, but may suffer from serious problems if the… CONTINUE READING


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