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
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
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-citation
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)
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
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.
