Scene recognition with omnidirectional vision for topological map using lightweight adaptive descriptors
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Date
2009Type
- Conference Paper
ETH Bibliography
yes
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Abstract
Mobile robots rely on their ability of scene recognition to build a topological map of the environment and perform location-related tasks. In this paper, we describe a novel lightweight scene recognition method using an adaptive descriptor which is based on color features and geometric information for omnidirectional vision. Our method enables the robot to add nodes to a topological map automatically and solve the localization problem of mobile robot in realtime. The descriptor of a scene is extracted in the YUV color space and its dimension is adaptive depending on the segmentation result of the panoramic image. Furthermore, the descriptor is invariant to rotation and slight changes of illumination. The robustness of the scene matching and recognition is tested through real experiments in a dynamic indoor environment. The experiment is carried out on a mobile robot equipped with an omnidirectional camera. In our tests, the average processing time is 30 ms for each frame including feature extraction, matching, and the adding of new nodes. Show more
Permanent link
https://doi.org/10.3929/ethz-a-010035843Publication status
publishedExternal links
Book title
2009 IEEE/RSJ International Conference on Intelligent Robots and SystemsPages / Article No.
Publisher
IEEEEvent
Organisational unit
03737 - Siegwart, Roland Y. / Siegwart, Roland Y.
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ETH Bibliography
yes
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