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Cited by 847

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Fast 3D recognition and pose using the Viewpoint Feature Histogram

Rusu, R B, Bradski, G, Thibaux, R, Hsu, J·2010·2010 IEEE/RSJ International Conference on Intelligent Robots and Systems
DOI 10.1109/iros.2010.5651280
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Abstract

We present the Viewpoint Feature Histogram (VFH), a descriptor for 3D point cloud data that encodes geometry and viewpoint. We demonstrate experimentally on a set of 60 objects captured with stereo cameras that VFH can be used as a distinctive signature, allowing simultaneous recognition of the object and its pose. The pose is accurate enough for robot manipulation, and the computational cost is low enough for real time operation. VFH was designed to be robust to large surface noise and missing depth information in order to work reliably on stereo data.

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Metadata

Authors
Rusu, R. B., Bradski, G., Thibaux, R., & Hsu, J.
Venue
2010 IEEE/RSJ International Conference on Intelligent Robots and Systems
Publisher
IEEE
Published
2010-10
Pages
2155-2162
DOI
10.1109/iros.2010.5651280
OpenAlex
W2033574012
Cited by
847
References
0
FWCI
36.84
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Fast 3D recognition and pose using the Viewpoint Feature Histogram. https://app.cochat.ai/papers/10.1109/iros.2010.5651280
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Rusu, R. B., Bradski, G., Thibaux, R., & Hsu, J. (2010). Fast 3D recognition and pose using the Viewpoint Feature Histogram. 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems. https://doi.org/10.1109/iros.2010.5651280

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.