The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A Benchmark for the Comparison of 3-D Motion Segmentation Algorithms
Abstract
Over the past few years, several methods for segmenting a scene containing multiple rigidly moving objects have been proposed. However, most existing methods have been tested on a handful of sequences only, and each method has been often tested on a different set of sequences. Therefore, the comparison of different methods has been fairly limited. In this paper, we compare four 3D motion segmentation algorithms for affine cameras on a benchmark of 155 motion sequences of checkerboard, traffic, and articulated scenes.
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Fischler, M. A., & Bolles, R. C. (1981) · Communications of the ACM · doi:10.1145/358669.358692 · Cited by 25,893
Cited by
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Lin, Z., Liu, R., & Su, Z. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1109.0367 · Cited by 992
Smooth Representation Clustering
Hu, H., Lin, Z., Feng, J., & Zhou, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.484 · Cited by 286
Learning Motion Patterns in Videos
Tokmakov, P., Alahari, K., & Schmid, C. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.64 · Cited by 267
Metadata
- Authors
- Tron, R., & Vidal, R.
- Venue
- 2007 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2007-06
- Pages
- 1-8
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2052311585
- Cited by
- 658
- References
- 1
- FWCI
- 16.15
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Tron, R., & Vidal, R. (2007). A Benchmark for the Comparison of 3-D Motion Segmentation Algorithms. 2007 IEEE Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.2007.382974
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