VR 2017

2017 IEEE Virtual Reality (VR), March 18-22, 2017, Los Angeles, CA, USA

Desktop Layout

Poster Session A
Posters
Ballroom A/B
Proposal of a Spectral Random Dots Marker using Local Feature for Posture Estimation
Norimasa Kobori, Daisuke Deguchi, Ichiro Ide, and Hiroshi Murase
(Toyota, Japan; Nagoya University, Japan)
Abstract: We propose a novel marker for robot's grasping task which has the following three aspects: (i) it is easy-to-find in a cluttered background, (ii) it is calculable for its posture (iii) its size is compact. The proposed marker is composed of a random dots pattern, and uses keypoint detection and a scale estimation by Spectral SIFT for dots detection and data decoding. The data is encoded by the scale size of dots, and the same dots in the marker work for both marker detection and data decoding. As a result, the proposed marker size can be compact. We confirmed the effectiveness of the proposed marker through experiments.

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Time stamp: 2019-11-13T13:03:31+01:00