Learning texture similarity with perceptual pairwise distance

Authors

Yan Gao, Nanyang Technological University, SingaporeFollow
Lei Wang, University of WollongongFollow
Kap Luk Chan, Nanyang Technological University, Singapore
Wei-Yan Yau, Institute for Infocomm Research Singapore

RIS ID

54396

Publication Details

Gao, Y., Wang, L., Chan, K. Luk. & Yau, W. (2005). Learning texture similarity with perceptual pairwise distance. Proceedings of the 4th International Workshop on Texture Analysis and Synthesis, in conjunction with the 10th IEEE International Conference on Computer Vision (ICCV) (pp. 83-88).

Abstract

In this paper, we demonstrate how texture classification and retrieval could benefit from learning perceptual pairwise distance of different texture classes. Textures as represented by certain image features may not be correctly compared in a way that is consistent with human perception. Learning similarity helps to alleviate this perceptual inconsistency. For textures, psychological experiments were shown to be able to construct perceptual pairwise distance matrix. We are going to show how this distance information could be utilized in learning similarity by Support Vector Machines for efficient texture classification and retrieval.