The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Local Trinary Patterns for human action recognition
Abstract
We present a novel action recognition method which is based on combining the effective description properties of Local Binary Patterns with the appearance invariance and adaptability of patch matching based methods. The resulting method is extremely efficient, and thus is suitable for real-time uses of simultaneous recovery of human action of several lengths and starting points. Tested on all publicity available datasets in the literature known to us, our system repeatedly achieves state of the art performance. Lastly, we present a new benchmark that focuses on uncut motion recognition in broadcast sports video.
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Cites
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
Ojala, T., Pietikainen, M., & Maenpaa, T. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2002.1017623 · Cited by 15,398
Robust Real-Time Face Detection
Viola, P., & Jones, M. J. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000013087.49260.fb · Cited by 14,097
Learning realistic human actions from movies
Laptev, I., Marszalek, M., Schmid, C., & Rozenfeld, B. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2008.4587756 · Cited by 3,444
Recognizing human actions: a local SVM approach
Schuldt, C., Laptev, I., & Caputo, B. (2004) · Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. · doi:10.1109/icpr.2004.1334462 · Cited by 3,010
Recognizing human actions: A local SVM approach
Schüldt, C., Laptev, I., & Barbara Caputo, B. (2004) · Cited by 2,908
Real-time tracking of non-rigid objects using mean shift
Comaniciu, D., Ramesh, V., & Meer, P. (2002) · Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662) · doi:10.1109/cvpr.2000.854761 · Cited by 2,906
Behavior Recognition via Sparse Spatio-Temporal Features
Dollar, P., Rabaud, V., Cottrell, G., & Belongie, S. (2006) · 2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance · doi:10.1109/vspets.2005.1570899 · Cited by 2,460
Robust real-time object detection.
Viola, P. A. (2001) · Cited by 2,340
A Spatio-Temporal Descriptor Based on 3D-Gradients
Klaeser, A., Marszalek, M., & Schmid, C. (2008) · Procedings of the British Machine Vision Conference 2008 · doi:10.5244/c.22.99 · Cited by 1,846
Blank, M., Gorelick, L., Shechtman, E., Irani, M., & Basri, R. (2005) · Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 · doi:10.1109/iccv.2005.28 · Cited by 1,733
Cited by
Action Recognition with Improved Trajectories
Wang, H., & Schmid, C. (2013) · 2013 IEEE International Conference on Computer Vision · doi:10.1109/iccv.2013.441 · Cited by 3,407
Dense Trajectories and Motion Boundary Descriptors for Action Recognition
Wang, H., Kläser, A., Schmid, C., & Liu, C.-L. (2013) · International Journal of Computer Vision · doi:10.1007/s11263-012-0594-8 · Cited by 1,669
A database for fine grained activity detection of cooking activities
Rohrbach, M., Amin, S., Andriluka, M., & Schiele, B. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6247801 · Cited by 521
Violence detection using Oriented VIolent Flows
Gao, Y., Liu, H., Sun, X., Wang, C., & Liu, Y. (2016) · Image and Vision Computing · doi:10.1016/j.imavis.2016.01.006 · Cited by 283
First Person Action Recognition Using Deep Learned Descriptors
Singh, S., Arora, C., & Jawahar, C. V. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.287 · Cited by 192
Metadata
- Authors
- Yeffet, L., & Wolf, L.
- Venue
- 2009 IEEE 12th International Conference on Computer Vision
- Publisher
- IEEE
- Published
- 2009-09
- Pages
- 492-497
- OpenAlex
- W2109761267
- Cited by
- 339
- References
- 25
- FWCI
- 21.26
- Type
- conference paper
- Language
- en
- Open access
- closed
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