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Three-dimensional registration using range and intensity information:
Abstract
The determination of relative pose between two range images, also called registration, is a ubiquitous problem in computer vision, for geometric model building as well as dimensional inspection. The method presented in this paper takes advantage of the ability of many active optical range sensors to record intensity or even color in addition to the range information. This information is used to improve the registration procedure by constraining potential matches between pairs of points based on a similarity measure derived from the intensity information. One difficulty in using the intensity information is its dependence on the measuring conditions such as distance and orientation. The intensity or color information must first be converted into a viewpoint-independent feature. This can be achieved by inverting an illumination model, by differential feature measurements or by simple clustering. Following that step, a robust iterative closest point method is then used to perform the pose determination. Using the intensity can help to speed up convergence or, in cases of remaining degrees of freedom (e.g. on images of a sphere), to additionally constrain the match. The paper will describe the algorithmic framework and provide examples using range-and-color images.
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Cited by
Efficient variants of the ICP algorithm
Rusinkiewicz, S., & Levoy, M. (2002) · Proceedings Third International Conference on 3-D Digital Imaging and Modeling · doi:10.1109/im.2001.924423 · Cited by 3,945
A Review of Point Cloud Registration Algorithms for Mobile Robotics
Pomerleau, F., Colas, F., & Siegwart, R. (2015) · Foundations and Trends® in Robotics · doi:10.1561/2300000035 · Cited by 717
RPM-Net: Robust Point Matching Using Learned Features
Yew, Z. J., & Lee, G. H. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.01184 · Cited by 615
Multiview registration for large data sets
Pulli, K. (2003) · Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062) · doi:10.1109/im.1999.805346 · Cited by 559
Least squares 3D surface and curve matching
Gruen, A., & Akca, D. (2005) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2005.02.006 · Cited by 536
Metadata
- Authors
- Godin, G., Rioux, M., & Baribeau, R.
- Venue
- SPIE Proceedings
- Publisher
- SPIE
- Published
- 1994-10-06
- Volume
- 2350
- Pages
- 279-290
- ISSN
- 0277-786X (ISSN-L)
- OpenAlex
- W2147545414
- Cited by
- 159
- References
- 0
- FWCI
- 1.62
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Three-dimensional registration using range and intensity information:. https://app.cochat.ai/papers/10.1117/12.189139
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- Godin, G., Rioux, M., & Baribeau, R. (1994). Three-dimensional registration using range and intensity information:. SPIE Proceedings. https://doi.org/10.1117/12.189139
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