Feature detector and descriptor evaluation in human action recognition

CIVR 2010 - 2010 ACM International Conference on Image and Video Retrieval

Volumn , Issue , 2010, Pages 477-484

  Shao, Ling ^a,b   Mattivi, Riccardo ^c  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

^b INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^c UNIVERSITY OF TRENTO   (Italy)

Author keywords

Bag of words; Feature descriptors; Feature detectors; Human action recognition; LBP TOP

Indexed keywords

BAG OF WORDS; FEATURE DESCRIPTORS; FEATURE DETECTOR; HUMAN-ACTION RECOGNITION; LBP-TOP;

GESTURE RECOGNITION; THREE DIMENSIONAL;

DETECTORS;

EID: 77955894382     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1816041.1816111     Document Type: Conference Paper

References (30)

1. A. A. Efros, A. C. Berg, G. Mori, and J. Malik. Recognizing action at a distance. In Proceedings of the Ninth IEEE International Conference on Computer Vision, pp.726-733, vol.2, 13-16 Oct, 2003.
2. E. Shechtman and M. Irani Space-time behavior based correlation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 405-412, vol. 1, 20-25 June, 2005.
3. S. Ali, A. Basharat, and M. Shah. Chaotic invariants for human action recognition. In Proc. of IEEE International Conference on Computer Vision (ICCV), pages 1-8, 2007.
4. K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir and L. Van Gool. A comparison of affine region detectors. International Journal of Computer Vision, vol. 65(1/2): 43-72, 2005.
5. K. Mikolajczyk and C. Schmid. A performance evaluation of local descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.27, no.10, pp.1615-1630, Oct. 2005
6. H. Ning, Y. Hu, and T.S. Huang. Searching Human Behaviors using Spatial-Temporal words. In Proceedings of IEEE International Conference on Image Processing, vol.6, pp. VI-337-VI-340, September-October, 2007.
7. T. Serre, L. Wolf, and T. Poggio. Object recognition with features inspired by visual cortex. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 994-1000, 2005.
8. D. G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision (IJCV), 60(2):91-110, 2004.
9. L. Fei-Fei and P. Perona. A Bayesian Hierarchical Model for Learning Natural Scene Categories. In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 524-531, 2005.
10. W. Cheung and G. Hamarneh. N-sift: N-dimensional scale invariant feature transform for matching medical images. In Proceedings of the 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 720-723, 2007.
11. T. Ojala, M. Pietikanen, and D. Harwood. A comparative study of texture measures with classification based on featured distribution. Pattern Recognition, 29(1):51-59, 1996.
12. T. Ojala, M. Pietikäinen, and T. Mäenpää. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24 (7), pp. 971-987, 2002.
13. T. Ahonen, A. Hadid, M. Pietikäinen. Face recognition with local binary pattern. In Proceedings of European Conference on Computer Vision (ECCV), 2004.
14. T. Ahonen, A. Hadid, and M. Pietikainen. Face Description with Local Binary Patterns: Application to Face Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, no.12, pp.2037-2041, December 2006.
15. G. Zhao and M. Pietikäinen. Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, no.6, pp.915-928, June 2007.
16. M. Heikkila, M. Pietikainen, and C. Schmid. Description of interest regions with center-symmetric local binary patterns. In Proceedings of the 5th Indian Conference on Computer Vision, Graphics and Image Processing, 2006
17. C. Schuldt, I. Laptev, and B. Caputo. Recognizing human actions: a local SVM approach. In Proceedings of the 17th International Conference on Pattern Recognition, pages 32-36, Vol.3, August 2004.
18. P. Dollar, V. Rabaud, G. Cottrell, and S. J. Belongie. Behavior recognition via sparse spatio-temporal features. In Proc. of ICCV Int. work-shop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance (VSPETS), pages 65-72, 2005.
19. I. Laptev and T. Lindeberg. Local descriptors for spatio-temporal recognition. In Proceedings of ECCV Workshop on Spatial Coherence for Visual Motion Analysis, pages 91-103, 2004.
20. C. Harris and M. Stephens. A combined corner and edge detector. In Proceedings of Alvey Vision Conference, pp. 147-152, 1998.
21. I. Laptev. On space-time interest points. International Journal of Computer Vision (IJCV), 64(2-3):107-123, 2005.
22. I. Laptev, M. Marszalek, C. Schmid, and B. Rozenfeld. Learning realistic human actions from movies. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, vol., no., pp.1-8, June 2008. Website: http://www.irisa.fr/vista/actions/.
23. H. Wang, M. Ullah, A. Klaser, I. Laptev, C. Schmid. Evaluation of local spatio-temporal features for action recognition. In Proceedings of the British Machine Vision Conference, September 2009.
24. P. Scovanner, S. Ali and M. Shah. A 3-dimensional sift descriptor and its application to action recognition. In Proceedings of the 15th ACM International Conference on Multimedia, September 2007. Website: http://www.cs.ucf.edu/ ~pscovann/
25. M. Heikkilä, M. Pietikäinen and C. Schmid. Description of interest regions with local binary patterns. Pattern Recognition, vol. 42(3), pp. 425-436, March 2007.
26. S. F. Wong and R. Cipolla. Extracting spatiotemporal interest points using global information. In Proc. of IEEE International Conference on Computer Vision (ICCV), pp. 1-8, 2007.
27. J. C. Niebles, H. Wang, and L. Fei-Fei. Unsupervised learning of human action categories using spatial-temporal words. In Proceedings of the British Machine Vision Conference, 2006.
28. C.-C. Chang and C.-J. Lin. LIBSVM: a library for support vector machines, 2001. Software available at: http://www.csie.ntu.edu.tw/~cjlin/libsvm.
29. M. Marszalek, I. Laptev, C. Schmid. Actions in Context. In Proceedings of IEEE Conference on Computer Vision & Pattern Recognition, 2009.
30. R. Mattivi and L. Shao. Human action recognition using LBP-TOP as sparse spatio-temporal feature descriptor. In Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (CAIP), Munster, Germany, September 2009.