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Proceedings Paper

Depth aspect images for robust object recognition
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Paper Abstract

In order to gain generality, robustness and efficiency in search, a novel search is proposed based on a representation called `Depth aspect image' is proposed as a controllable two-dimensional representation of local depth distribution used in cooperation with a distinct `Voxel framing', which enables effective reference coordination without any prominent features, such as vertices or edges. A robust statistical estimator called `Least quantile of residuals' is furthermore introduced for robust matching, which can be utilized for both depth matching and model verification. Since the proposed method is of model-based approach with possible views of local structures, the computation cost for matching has to be reduced by introducing random sampling and an effective hashing. Experiments with real scenes show the effectiveness of the proposed method.

Paper Details

Date Published: 30 September 2003
PDF: 12 pages
Proc. SPIE 5264, Optomechatronic Systems IV, (30 September 2003); doi: 10.1117/12.515182
Show Author Affiliations
Tomoyuki Takeguchi, Hokkaido Univ. (Japan)
Shun'ichi Kaneko, Hokkaido Univ. (Japan)


Published in SPIE Proceedings Vol. 5264:
Optomechatronic Systems IV
George K. Knopf, Editor(s)

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