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Computational framework for determining stereo correspondence from a set of linear spatial filters
Abstract
We present a computational framework for stereopsis based on the outputs of linear spatial filters tuned to a range of orientations and scales. This approach goes beyond edge-based and area-based approaches by using a richer image description and incorporating several stereo cues that have previously been neglected in the computer vision literature.
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Cited by
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
Scharstein, D., & Szeliski, R. (2002) · International Journal of Computer Vision · doi:10.1023/a:1014573219977 · Cited by 6,740
Shape matching and object recognition using shape contexts
Belongie, S., Malik, J., & Puzicha, J. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.993558 · Cited by 6,306
Self-citationModeling and rendering architecture from photographs: a hybrid geometry- and image-based approach
Debevec, P. E., Taylor, C. J., & Malik, J. (1996) · Proceedings of the 23rd annual conference on Computer graphics and interactive techniques · doi:10.1145/237170.237191 · Cited by 1,905
Self-citationRepresenting and Recognizing the Visual Appearance of Materials Using Three-Dimensional Textons
Leung, T., & Malik, J. (2001) · International Journal of Computer Vision · doi:10.1023/a:1011126920638 · Cited by 1,498
Self-citationDeictic codes for the embodiment of cognition
Ballard, D. H., Hayhoe, M. M., Pook, P. K., & Rao, R. P. N. (1997) · Behavioral and Brain Sciences · doi:10.1017/s0140525x97001611 · Cited by 1,082
Metadata
- Authors
- Jones, D. G., & Malik, J.
- Venue
- Image and Vision Computing
- Publisher
- Elsevier BV
- Published
- 1992-12
- Volume
- 10
- Issue
- 10
- Pages
- 699-708
- ISSN
- 0262-8856 (ISSN-L)
- OpenAlex
- W2106883675
- Cited by
- 191
- References
- 0
- FWCI
- 14.75
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
