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Cited by 351

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Ensemble of shape functions for 3D object classification

Wohlkinger, Walter, Vincze, Markus·2011·2011 IEEE International Conference on Robotics and Biomimetics

Abstract

This work addresses the problem of real-time 3D shape based object class recognition, its scaling to many categories and the reliable perception of categories. A novel shape descriptor for partial point clouds based on shape functions is presented, capable of training on synthetic data and classifying objects from a depth sensor in a single partial view in a fast and robust manner. The classification task is stated as a 3D retrieval task finding the nearest neighbors from synthetically generated views of CAD-models to the sensed point cloud with a Kinect-style depth sensor. The presented shape descriptor shows that the combination of angle, point-distance and area shape functions gives a significant boost in recognition rate against the baseline descriptor and outperforms the state-of-the-art descriptors in our experimental evaluation on a publicly available dataset of real-world objects in table scene contexts with up to 200 categories.

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Crossref · 10.1109/robio.2011.6181760

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Metadata

Authors
Wohlkinger, W., & Vincze, M.
Venue
2011 IEEE International Conference on Robotics and Biomimetics
Publisher
IEEE
Published
2011-12
Pages
2987-2992
OpenAlex
W2041469568
Cited by
351
References
10
FWCI
18.24
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Ensemble of shape functions for 3D object classification. https://app.cochat.ai/papers/10.1109/robio.2011.6181760
The paper
Wohlkinger, W., & Vincze, M. (2011). Ensemble of shape functions for 3D object classification. 2011 IEEE International Conference on Robotics and Biomimetics. https://doi.org/10.1109/robio.2011.6181760

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