Classifying web videos using a global video descriptor

Machine Vision and Applications

Volumn 24, Issue 7, 2013, Pages 1473-1485

  Solmaz, Berkan ^a   Assari, Shayan Modiri ^a   Shah, Mubarak ^a  

^a UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

Action recognition; Frequency spectrum; Spatio temporal analysis; Video descriptors

Indexed keywords

MOTION ESTIMATION; PATTERN RECOGNITION; SPECTROSCOPY; VIDEO RECORDING;

ACTION RECOGNITION; CLASSIFICATION ACCURACY; DESCRIPTORS; DISCRIMINATIVE POWER; FREQUENCY SPECTRA; HUMAN MOTION RECOGNITION; SPATIO-TEMPORAL FILTER; SPATIOTEMPORAL ANALYSIS;

CLASSIFICATION (OF INFORMATION);

EID: 84885330892     PISSN: 09328092     EISSN: 14321769     Source Type: Journal    
DOI: 10.1007/s00138-012-0449-x     Document Type: Article

References (27)

1. Schuldt, C.; Laptev, I.; Caputo, B.: Recognizing human actions: a local svm approach. In: Proceedings of the 17th international conference on, pattern recognition (ICPR'04), vol. 3, pp. 32-36 (2004)
2. http://vision.eecs.ucf.edu/datasetsActions.html
3. Kuehne, H.; Jhuang, H.; Garrote, E.; Poggio, T.; Serre, T.: HMDB: a large video database for human motion recognition. In: ICCV (2011)
4. Poppe, R.: A survey on vision-based human action recognition. Image Vision Comput. 28, 976-990 (2010)
5. Weinland, D.; Ronfard, R.; Boyer, E.: A survey of vision-based methods for action representation, segmentation and recognition. Comput. Vis. Image Underst. 115, 224-241 (2011)
6. Laptev, I.; Marszalek, M.; Schmid, C.; Rozenfeld, B.: Learning realistic human actions from movies. In: IEEE Computer Society conference on computer vision and, pattern recognition (CVPR '08) (2008)
7. Liu, J.; Luo, J.; Shah, M.: Recognizing realistic actions from videos in the wild. In: IEEE conference on computer vision and, pattern recognition (CVPR '09), pp. 1996-2003 (2009)
8. Bobick, A.; Davis, J.: The recognition of human movement using temporal templates. IEEE Trans. Pattern Anal. Mach. Intell. 23, 257-267 (2001)
9. Yilmaz, A.; Shah, M.: A differential geometric approach to representing the human actions. Comput. Vis. Image Underst. 109, 335-351 (2008)
10. Black, M.: Explaining optical flow events with parameterized spatio-temporal models. In: IEEE Computer Society conference on computer vision and, pattern recognition (CVPR '99), vol. 1, pp. 326-332 (1999)
11. Polana, R.; Nelson, R.C.: Detection and recognition of periodic, non-rigid motion. Int. J. Comput. Vision 23, 261-282 (1997)
12. Wu, S.; Oreifej, O.; Shah, M.: Action recognition in videos acquired by a moving camera using motion decomposition of lagrangian particle trajectories. In: IEEE international conference on computer vision (ICCV '11), pp. 1419-1426 (2011)
13. Wang, H.; Klaser, A.; Schmid, C.; Liu, C.L.: Action recognition by dense trajectories. In: IEEE conference on computer vision and, pattern recognition (CVPR '11), pp. 3169-3176 (2011)
14. Laptev, I.: On space-time interest points. Int. J. Comput. Vision 64, 107-123 (2005)
15. Harris, C.; Stephens, M.: A combined corner and edge detector. In: Proceedings of fourth Alvey vision conference, pp. 147-151 (1988)
16. Dollar, P.; Rabaud, V.; Cottrell, G.; Belongie, S.: Behavior recognition via sparse spatio-temporal features. In: VS-PETS, pp. 65-72 (2005)
17. Klaser, A.; Marszalek, M.; Schmid, C.: A spatio-temporal descriptor based on 3d-gradients. BMVC, In (2008)
18. Scovanner, P.; Ali, S.; Shah, M.: A 3-dimensional SIFT descriptor and its application to action recognition. In: ACM multimedia, pp. 357-360 (2007)
19. Ikizler-Cinbis, N.; Sclaroff, S.: Object, scene and actions: combining multiple features for human action recognition. In: Proceedings of the 11th European conference on computer vision (ECCV '10), pp. 494-507 (2010)
20. Oliva, A.; Torralba, A.B.; Guerin-Dugue, A.; Herault, J.: Global semantic classification of scenes using power spectrum templates. Challenge of image retrieval, pp. 1-12 (1999)
21. Oliva, A.; Torralba, A.: Modeling the shape of the scene: a holistic representation of the spatial envelope. Int. J. Comput. Vision 42, 145-175 (2001)
22. Heeger, D.J.: Notes on motion estimation. http://white.stanford.edu/ ~heeger (1998)
23. Maaten, L.V.D.; Postma, E.O.; Herik, H.J.V.D.: Dimensionality reduction: a comparative review (2008)
24. Wang, H.; Ullah, M.M.; Klaser, A.; Laptev, I.; Schmid, C.: Evaluation of local spatio-temporal features for action recognition. In: BMVC, p. 127 (2009)
25. Chang, C.C.; Lin, C.J.: LIBSVM: A library for support vector machines. ACM Trans. Intell. Syst. Technol. 2, 27:1-27:27 (2011)
26. Jhuang, H.; Serre, T.; Wolf, L.; Poggio, T.: A biologically inspired system for action recognition. In: IEEE 11th international conference on computer vision (ICCV'07), pp. 1-8 (2007)
27. Gilbert, A.; Illingworth, J.; Bowden, R.: Action recognition using mined hierarchical compound features. IEEE Trans. Pattern Anal. Mach. Intell. 33, 883-897 (2011)