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Place recognition based on saliency for topological localization

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Abstract

Based on salient visual regions for mobile robot navigation in unknown environments, a new place recognition system was presented. The system uses monocular camera to acquire omni-directional images of the environment where the robot locates. Salient local regions are detected from these images using center-surround difference method, which computes opponencies of color and texture among multi-scale image spaces. And then they are organized using hidden Markov model (HMM) to form the vertex of topological map. So localization, that is place recognition in our system, can be converted to evaluation of HMM. Experimental results show that the saliency detection is immune to the changes of scale, 2D rotation and viewpoint etc. The created topological map has smaller size and a higher ratio of recognition is obtained.

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Authors and Affiliations

  1. School of Information Science and Engineering, Central South University, 410083, Changsha, China

    Wang Lu (Doctoral candidate) & Cai Zi-xing

  2. Department of Computer Science, Zhongyuan Institute of Technology, 450007, Zhengzhou, China

    Wang Lu (Doctoral candidate)

Authors
  1. Wang Lu
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  2. Cai Zi-xing
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Correspondence to Wang Lu.

Additional information

Foundation item: Projects(60234030, 60404021) supported by the National Natural Science Foundation of China

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Wang, L., Cai, Zx. Place recognition based on saliency for topological localization. J Cent. South Univ. Technol. 13, 536–541 (2006). https://doi.org/10.1007/s11771-006-0083-8

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  • DOI: https://doi.org/10.1007/s11771-006-0083-8

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