Depth aspect images for robust object recognition

Tomoyuki Takeguchi; Shun'ichi Kaneko

doi:10.1117/12.515182

30 September 2003 Depth aspect images for robust object recognition

Proceedings Volume 5264, Optomechatronic Systems IV; (2003) https://doi.org/10.1117/12.515182
Event: Photonics Technologies for Robotics, Automation, and Manufacturing, 2003, Providence, RI, United States

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.

Citation Download Citation

Tomoyuki Takeguchi and Shun'ichi Kaneko "Depth aspect images for robust object recognition", Proc. SPIE 5264, Optomechatronic Systems IV, (30 September 2003); https://doi.org/10.1117/12.515182

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