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Robust Feature Detection for a Mobile Robot using a Multi-View Single Camera

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3 Author(s)
Jegoon Ryu ; Grad. Sch. of IPS, Waseda Univ., Fukuoka ; Deng Zhang ; Nishimura, T.

In this paper, we present a multi-view single camera and a novel model of scale and illumination invariant corner detection for a service robot in indoor environment. Vision-based simultaneous localization and mapping (VSLAM) has received much attention. It is used for VSLAM that are single cameras, multiple cameras in a stereo setup or omni-directional cameras. We propose a different approach which multiple mirrors are mounted on a vision system in a single-view-point (SVP) configuration. This vision system is easily to acquire no distortion image sequences without any preprocessing. Robust feature detection method is also described for VSLAM of a service robot in indoor environment. This method can detect scale and illumination invariant corner features in any environment.

Published in:

System Integration, 2008 IEEE/SICE International Symposium on

Date of Conference:

4-4 Dec. 2008