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Extended Gaussian images
Abstract
This is a primer on extended Gaussian images. Extended Gaussian images are useful for representing the shapes of surfaces. They can be computed easily from: 1. needle maps obtained using photometric stereo; or 2. depth maps generated by ranging devices or binocular stereo. Importantly, they can also be determined simply from geometric models of the objects. Extended Gaussian images can be of use in at least two of the tasks facing a machine vision system: 1. recognition, and 2. determining the attitude in space of an object. Here, the extended Gaussian image is defined and some of its properties discussed. An elaboration for nonconvex objects is presented and several examples are shown.
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Cited by
A method for registration of 3-D shapes
Besl, P. J., & McKay, N. D. (1992) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.121791 · Cited by 18,103
Rotation invariant spherical harmonic representation of 3D shape descriptors
Kazhdan, M. M., Funkhouser, T. A., & Rusinkiewicz, S. M. (2003) · doi:10.5555/882370.882392 · Cited by 1,202
Funkhouser, T., Min, P., Kazhdan, M., Chen, J., Halderman, A., Dobkin, D., & Jacobs, D. (2003) · ACM Transactions on Graphics · doi:10.1145/588272.588279 · Cited by 935
Pointwise Convolutional Neural Networks
Hua, B.-S., Tran, M.-K., & Yeung, S.-K. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00109 · Cited by 615
Model-based recognition in robot vision
Chin, R. T., & Dyer, C. R. (1986) · ACM Computing Surveys · doi:10.1145/6462.6464 · Cited by 567
Metadata
- Authors
- Horn, B. K. P.
- Venue
- Proceedings of the IEEE
- Published
- 1984
- Volume
- 72
- Issue
- 12
- Pages
- 1671-1686
- ISSN
- 0018-9219 (ISSN-L)
- OpenAlex
- W2053939793
- Cited by
- 670
- References
- 0
- FWCI
- 15.66
- Type
- journal article
- Language
- en
- Open access
- closed
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