The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Local feature view clustering for 3D object recognition
Abstract
There have been important recent advances in object recognition through the matching of invariant local image features. However, the existing approaches are based on matching to individual training images. This paper presents a method for combining multiple images of a 3D object into a single model representation. This provides for recognition of 3D objects from any viewpoint, the generalization of models to non-rigid changes, and improved robustness through the combination of features acquired under a range of imaging conditions. The decision of whether to cluster a training image into an existing view representation or to treat it as a new view is based on the geometric accuracy of the match to previous model views. A new probabilistic model is developed to reduce the false positive matches that would otherwise arise due to loosened geometric constraints on matching 3D and non-rigid models. A system has been developed based on these approaches that is able to robustly recognize 3D objects in cluttered natural images in sub-second times.
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Cites
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Self-citationIndexing based on scale invariant interest points
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Shape indexing using approximate nearest-neighbour search in high-dimensional spaces
Beis, J. S., & Lowe, D. G. (2002) · Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1997.609451 · Cited by 879
Self-citationRecognition by linear combinations of models
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Cited by
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
Self-citationVideo Google: a text retrieval approach to object matching in videos
Sivic, & Zisserman (2003) · Proceedings Ninth IEEE International Conference on Computer Vision · doi:10.1109/iccv.2003.1238663 · Cited by 6,367
Efficient Visual Search of Videos Cast as Text Retrieval
Sivic, J., & Zisserman, A. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.111 · Cited by 499
Monocular model-based 3D tracking of rigid objects: a survey
Lepetit, V., & Fua, P. (2005) · Foundations and Trends® in Computer Graphics and Vision · doi:10.1561/0600000001 · Cited by 484
Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation
Kehl, W., Milletari, F., Tombari, F., Ilic, S., & Navab, N. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46487-9_13 · Cited by 283
Metadata
- Authors
- Lowe, D. G.
- Venue
- Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001
- Publisher
- IEEE Comput. Soc
- Published
- 2005-08-25
- Volume
- 1
- Pages
- I-682-I-688
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2162601563
- Cited by
- 482
- References
- 17
- FWCI
- 22.14
- Type
- conference paper
- Language
- en
- Open access
- closed
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