Robust place recognition by spectral graph matching using omni-directional images

This paper presents an appearance based place recognition method using omni-directional images which describe 360° panoramic scene around a camera at one time. We utilize a spectral graph matching method to measure a degree of similarity between omni-directional query and topological node images. This method builds an affinity matrix of a graph whose nodes represent the potential correspondences while the weights on the edges measure the similarity between pairs of potential correspondences. In this paper, we compute the elements of affinity matrix with individual photometric feature matching and geometrical graph shape matching between omni-directional images. The proposed method enables robust place recognition since it considers both the geometrical and photometrical similarities. The experimental results show that the proposed method can robustly estimate the place in the dynamic indoor environment.