Cubistic Representation for Real-Time 3D Shape and Pose Estimation of Unknown Rigid Object

Hiromasa Yoshimoto, Yuichi Nakamura; Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops, 2013, pp. 522-529

Abstract


This paper introduces Cubistic Representation as a novel 3D surface shape model. Cubistic representation is a set of 3D surface fragments; each fragment contains subject's 3D surface shape and its color and redundantly covers the subject surface. By laminating these fragments using a given pose parameter, the subject's appearance can be synthesized. Using cubistic representation, we propose a real-time 3D rigid object tracking approach by acquiring the 3D surface shape and its pose simultaneously. We use the particle filter scheme for both shape and pose estimation; each fragment is used as a partial shape hypothesis and is sampled and refined by a particle filter. We also use the RANSAC algorithm to remove wrong fragments as outliers to refine the shape. We also implemented an online demonstration system with GPU and a Kinect sensor and evaluated the performance of our approach in a real environment.

Related Material


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[bibtex]
@InProceedings{Yoshimoto_2013_ICCV_Workshops,
author = {Hiromasa Yoshimoto and Yuichi Nakamura},
title = {Cubistic Representation for Real-Time 3D Shape and Pose Estimation of Unknown Rigid Object},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {June},
year = {2013}
}