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Diffusion Distance for Histogram Comparison
2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06)
In this paper we propose diffusion distance, a new dissimilarity measure between histogram-based descriptors. We define the difference between two histograms to be a temperature field. We then study the relationship between histogram similarity and a diffusion process, showing how diffusion handles deformation as well as quantization effects. As a result, the diffusion distance is derived as the sum of dissimilarities over scales. Being a cross-bin histogram distance, the diffusion distance is
doi:10.1109/cvpr.2006.99
dblp:conf/cvpr/LingO06
fatcat:g7amkxgklnhr5lrfmimcyllfym