The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The Robust Estimation of Multiple Motions: Parametric and Piecewise-Smooth Flow Fields
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Citations
Cites
Computation of component image velocity from local phase information
Fleet, D. J., & Jepson, A. D. (1990) · International Journal of Computer Vision · doi:10.1007/bf00056772 · Cited by 1,085
Cited by
A Database and Evaluation Methodology for Optical Flow
Baker, S., Scharstein, D., Lewis, J. P., Roth, S., Black, M. J., & Szeliski, R. (2011) · International Journal of Computer Vision · doi:10.1007/s11263-010-0390-2 · Cited by 2,205
“The algorithm by Black and Anandan (1996 ) a lso uses afi rstorder prior, but can use an arbitrary robust penalty function on the prior term rather than the L2 norm in (9).”
BackgroundMethodInfluentialSelf-citationLarge Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation
Brox, T., & Malik, J. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.143 · Cited by 1,295
Lucas/Kanade Meets Horn/Schunck: Combining Local and Global Optic Flow Methods
Bruhn, A., Weickert, J., & Schnörr, C. (2005) · International Journal of Computer Vision · doi:10.1023/b:visi.0000045324.43199.43 · Cited by 1,160
A survey of appearance models in visual object tracking
Li, X., Hu, W., Shen, C., Zhang, Z., Dick, A., & Hengel, A. V. D. (2013) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/2508037.2508039 · Cited by 705
A Database and Evaluation Methodology for Optical Flow
Baker, S., Roth, S., Scharstein, D., Black, M. J., Lewis, J. P., & Szeliski, R. (2007) · 2007 IEEE 11th International Conference on Computer Vision · doi:10.1109/iccv.2007.4408903 · Cited by 618
Self-citationRecognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image Motion
Black, M. J., & Yacoob, Y. (1997) · International Journal of Computer Vision · doi:10.1023/a:1007977618277 · Cited by 514
Self-citationIrani, M., & Anandan, P. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-44480-7_18 · Cited by 250
Self-citationMacro- and micro-expression spotting in long videos using spatio-temporal strain
Shreve, M., Godavarthy, S., Goldgof, D., & Sarkar, S. (2011) · Face and Gesture 2011 · doi:10.1109/fg.2011.5771451 · Cited by 218
Video quality assessment using a statistical model of human visual speed perception
Wang, Z., & Li, Q. (2007) · Journal of the Optical Society of America A · doi:10.1364/josaa.24.000b61 · Cited by 210
FusionFlow: Discrete-continuous optimization for optical flow estimation
Lempitsky, V., Roth, S., & Rother, C. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2008.4587751 · Cited by 145
Towards macro- and micro-expression spotting in video using strain patterns
Shreve, M., Godavarthy, S., Manohar, V., Goldgof, D., & Sarkar, S. (2009) · 2009 Workshop on Applications of Computer Vision (WACV) · doi:10.1109/wacv.2009.5403044 · Cited by 124
Zimmer, H., Bruhn, A., Weickert, J., Valgaerts, L., Salgado, A., Rosenhahn, B., & Seidel, H.-P. (2009) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-03641-5_16 · Cited by 107
On the spatial statistics of optical flow
Roth, S., & Black, M. J. (2005) · Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 · doi:10.1109/iccv.2005.180 · Cited by 95
Self-citationFrom simple innate biases to complex visual concepts
Ullman, S., Harari, D., & Dorfman, N. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1207690109 · Cited by 77
Analyzing Raman spectroscopic data
Ryabchykov, O., Guo, S., & Bocklitz, T. (2019) · Physical Sciences Reviews · doi:10.1515/psr-2017-0043 · Cited by 74
Optical flow estimation with uncertainties through dynamic MRFs
Glocker, B., Paragios, N., Komodakis, N., Tziritas, G., & Navab, N. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2008.4587562 · Cited by 69
Optical flow estimation on coarse-to-fine region-trees using discrete optimization
Lei, C., & Yang, Y.-H. (2009) · 2009 IEEE 12th International Conference on Computer Vision · doi:10.1109/iccv.2009.5459253 · Cited by 67
MemFlow: Optical Flow Estimation and Prediction with Memory
Dong, Q., & Fu, Y. (2024) · arXiv · doi:10.48550/arxiv.2404.04808 · Cited by 49
Metadata
- Authors
- Black, M. J., & Anandan, P.
- Venue
- Computer Vision and Image Understanding
- Publisher
- Elsevier BV
- Published
- 1996-01
- Volume
- 63
- Issue
- 1
- Pages
- 75-104
- ISSN
- 1077-3142 (ISSN-L)
- OpenAlex
- W2100315781
- Cited by
- 1,570
- References
- 1
- FWCI
- 28.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
