Riemannian Analysis of Probability Density Functions with Applications in Vision

  title={Riemannian Analysis of Probability Density Functions with Applications in Vision},
  author={Anuj Srivastava and Ian H. Jermyn and Shantanu H. Joshi},
  journal={2007 IEEE Conference on Computer Vision and Pattern Recognition},
Applications in computer vision involve statistically analyzing an important class of constrained, non-negative functions, including probability density functions (in texture analysis), dynamic time-warping functions (in activity analysis), and re-parametrization or non-rigid registration functions (in shape analysis of curves). For this one needs to impose a Riemannian structure on the spaces formed by these functions. We propose a "spherical" version of the Fisher-Rao metric that provides… CONTINUE READING
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  • volume 3757 of Lecture Notes in Computer Science…
  • 2005
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