Silhouette-based human action recognition using sequences of key poses

Pattern Recognition Letters

Volumn 34, Issue 15, 2013, Pages 1799-1807

  Chaaraoui, Alexandros Andre ^a   Climent Pérez, Pau ^a   Flórez Revuelta, Francisco ^b  

^a UNIVERSITY OF ALICANTE   (Spain)

^b KINGSTON UNIVERSITY   (United Kingdom)

Author keywords

Human action recognition; IXMAS dataset; Key pose; Key pose sequence; MuHAVi dataset; Weizmann dataset

Indexed keywords

SOFTWARE ENGINEERING;

HUMAN-ACTION RECOGNITION; IXMAS DATASET; KEY POSE; MUHAVI DATASET; WEIZMANN DATASET;

PATTERN RECOGNITION;

EID: 84885675164     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2013.01.021     Document Type: Article

References (45)

1. Aggarwal, J., Ryoo, M., 2011. Human activity analysis: A review. ACM Comput. Surv. 43, 16:1-16:43.
2. Angeles Mendoza, M., Pérez de la Blanca, N., 2007. Hmm-based action recognition using contour histograms. In: Martí, J., Benedí, J., MendonCa, A., Serrat, J. (Eds.), Pattern Recognition and Image Analysis, Lecture Notes in Computer Science, 4477. Springer, Berlin/Heidelberg, pp. 394-401.
3. Baysal, S., Kurt, M., Duygulu, P., 2010. Recognizing human actions using key poses. In: 20th Internat. Conf. on Pattern Recognition (ICPR), pp. 1727-1730.
4. Blank, M., Gorelick, L., Shechtman, E., Irani, M., Basri, R., 2005. Actions as space-time shapes. In: Tenth IEEE Internat. Conf. on Computer Vision, ICCV 2005, vol. 2, pp. 1395-1402. (Pubitemid 44042342)
5. Bobick, A., Davis, J., 2001. The recognition of human movement using temporal templates. IEEE Trans. Pattern Anal Machine Intell. 23, 257-267. (Pubitemid 32286632)
6. Bradski, G., 2000. The OpenCV Library. Dr. Dobb's Journal of Software Tools.
7. Bremond, F., 2007. Scene Understanding: perception, multi-sensor fusion, spatiotemporal reasoning and activity recognition, Ph.D. thesis, Université de Nice-Sophia Antipolis.
8. Chaaraoui, A.A., Climent-Pérez, P., Fló rez-Revuelta, F., 2012. A review on vision techniques applied to human behaviour analysis for ambient-assisted living. Exp. Systems Appl. 39, 10873-10888.
9. Cheema, S., Eweiwi, A., Thurau, C., Bauckhage, C., 2011. Action recognition by learning discriminative key poses. In: IEEE Internat. Conf. on Computer Vision Workshops (ICCV Workshops), pp. 1302-1309.
10. Cherla, S., Kulkarni, K., Kale, A., Ramasubramanian, V., 2008. Towards fast, viewinvariant human action recognition. In: IEEE Computer Society Conf. on Computer Vision and Pattern Recognition Workshops CVPRW '08, pp. 1-8.
11. Dedeoǧlu, Y., Töreyin, B., Güdükbay, U., Cetin, A., 2006. Silhouette-based method for object classification and human action recognition in video. In: Huang, T., Sebe, N., Lew, M., Pavlovic, V., Kölsch, M., Galata, A., Kisacanin, B. (Eds.), Computer Vision in Human-Computer Interaction, Lecture Notes in Computer Science, 3979. Springer, Berlin/Heidelberg, pp. 64-77. (Pubitemid 44059048)
12. Eweiwi, A., Cheema, S., Thurau, C., Bauckhage, C., 2011. Temporal key poses for human action recognition. In: IEEE Internat. Conf. on Computer Vision Workshops (ICCV Workshops) 2011, pp. 1310-1317.
13. Fathi, A., Mori, G., 2008. Action recognition by learning mid-level motion features. In: IEEE Conf. Computer Vision and Pattern Recognition, CVPR 2008, pp. 1-8.
14. HernAndez, J., Montemayor, A., Pantrigo, J., SAnchez, A., 2011. Human action recognition based on tracking features. In: FerrAndez, J., Alvarez SAnchez, J., de la Paz, F., Toledo, F. (Eds.), Foundations on Natural and Artificial Computation, Lecture Notes in Computer Science, 6686, pp. 471-480.
15. Holte, M.B., Tran, C., Trivedi, M.M., Moeslund, T.B., 2011. Human action recognition using multiple views: a comparative perspective on recent developments. In: Proc. of the 2011 Joint ACM Workshop on Human Gesture and Behavior Understanding. ACM, New York, NY, USA, pp. 47-52.
16. Holte, M., Chakraborty, B., Gonzalez, J., Moeslund, T., 2012. A local 3-d motion descriptor for multi-view human action recognition from 4-d spatio-temporal interest points. IEEE J. Selected Topics Signal Process. 6, 553-565.
17. Horprasert, T., Harwood, D., Davis, L., 1999. A statistical approach for real-time robust background subtraction and shadow detection. IEEE ICCV, 256-261.
18. Hu, W., Tan, T., Wang, L., Maybank, S., 2004. A survey on visual surveillance of object motion and behaviors. IEEE Trans. Systems Man Cybernet. 34, 334-352.
19. Ikizler, N., Duygulu, P., 2007. Human action recognition using distribution of oriented rectangular patches. In: Elgammal, A., Rosenhahn, B., Klette, R. (Eds.), Human Motion Understanding, Modeling, Capture and Animation, Lecture Notes in Computer Science, 4814. Springer, Berlin/Heidelberg, pp. 271-284.
20. Juan, L., Gwun, O., 2009. A comparison of SIFT, PCA-SIFT and SURF. Internat. J. Image Process. (IJIP) 3, 143-152.
21. Kadir, T., Brady, M., 2003. Scale saliency: A novel approach to salient feature and scale selection. In: Internat. Conf. on Visual Information Engineering VIE 2003, pp. 25-28.
22. Kim, K., Chalidabhongse, T.H., Harwood, D., Davis, L., 2005. Real-time foregroundbackground segmentation using codebook model. Real-Time Imaging 11, 172-185, Special Issue on Video Object Processing. (Pubitemid 40929458)
23. Kjellström (Sidenbladh), H., 2011. Contextual action recognition. In: Moeslund, T.B., Hilton, A., Krüger, V., Sigal, L. (Eds.), Visual Analysis of Humans, Springer, London, pp. 355-376.
24. Laptev, I., 2005. On space-time interest points. Internat. J. Comput. Vision 64, 107-123. (Pubitemid 41314645)
25. Martinez-Contreras, F., Orrite-Urunuela, C., Herrero-Jaraba, E., Ragheb, H., Velastin, S., 2009. Recognizing human actions using silhouette-based hmm. In: Sixth IEEE Internat. Conf. on Advanced Video and Signal Based Surveillance, AVSS '09, pp. 43-48.
26. Moeslund, T.B., Hilton, A., Krüger, V., 2006. A survey of advances in vision-based human motion capture and analysis. Computer Vision Image Understanding 104, 90-126. (Pubitemid 44573873)
27. Oikonomopoulos, A., Patras, I., Pantic, M., 2005. Spatiotemporal salient points for visual recognition of human actions. IEEE Trans. Systems Man Cybernet. 36, 710-719.
28. Poppe, R., 2010. A survey on vision-based human action recognition. Image Vision Comput. 28, 976-990.
29. Saghafi, B., Rajan, D., 2012. Human action recognition using pose-based discriminant embedding. Signal Process. Image Commun. 27, 96-111.
30. Schuldt, C., Laptev, I., Caputo, B., 2004. Recognizing human actions: A local svm approach. In: Proc. of the 17th Internat. Conf. on Pattern Recognition, ICPR 2004, vol. 3, pp. 32-36.
31. Scovanner, P., Ali, S., Shah, M., 2007. A 3-dimensional sift descriptor and its application to action recognition. In: Proc. 15th Internat. Conf. on Multimedia, ACM, New York, NY, USA, pp. 357-360.
32. Shao, L., Chen, X., 2010. Histogram of body poses and spectral regression discriminant analysis for human action categorization. In: British Machine Vision Conference (BMVC), Aberystwyth, UK.
33. Shotton, J., Fitzgibbon, A., Cook, M., Sharp, T., Finocchio, M., Moore, R., Kipman, A., Blake, A., 2011. Real-time human pose recognition in parts from single depth images. In: IEEE Conf. Computer Vision and Pattern Recognition (CVPR), pp. 1297-1304.
34. Singh, S., Velastin, S., Ragheb, H., 2010. Muhavi: A multicamera human action video dataset for the evaluation of action recognition methods. In: Seventh IEEE Internat. Conf. on Advanced Video and Signal Based Surveillance (AVSS), pp. 8-55.
35. Suzuki, S., be, K., 1985. Topological structural analysis of digitized binary images by border following. Comput. Vision Graphics Image Process. 30, 32-46. (Pubitemid 15490080)
36. Thurau, C., HlavAč, V., 2007. n-Grams of action primitives for recognizing human behavior. In: Kropatsch, W., Kampel, M., Hanbury, A. (Eds.), Computer Analysis of Images and Patterns, Lecture Notes in Computer Science, Springer, Berlin/ Heidelberg, vol. 4673, pp. 93-100.
37. Tran, D., Sorokin, A., 2008. Human activity recognition with metric learning. In: Forsyth, D., Torr, P., Zisserman, A. (Eds.), Computer Vision ECCV 2008, Lecture Notes in Computer Science, 5302. Springer, Berlin/Heidelberg, pp. 548-561.
38. Turaga, P., Chellappa, R., Subrahmanian, V., Udrea, O., 2008. Machine recognition of human activities: A survey. IEEE Trans. Circuits Systems Video Technol. 18, 1473-1488.
39. Wang, J., She, M., Nahavandi, S., Kouzani, A., 2010. A review of vision-based gait recognition methods for human identification. In: Internat. Conf. on Digital Image Computing: Techniques and Applications (DICTA) 2010, pp. 320-327.
40. Weinland, D., Ronfard, R., Boyer, E., 2006. Free viewpoint action recognition using motion history volumes. Computer Vision Image Understanding 104, 249-257. (Pubitemid 44573869)
41. Weinland, D., Özuysal, M., Fua, P., 2010. Making action recognition robust to occlusions and viewpoint changes. In: Daniilidis, K., Maragos, P., Paragios, N. (Eds.), Computer Vision ECCV 2010, Lecture Notes in Computer Science, vol. 6313, Springer, Berlin/Heidelberg, pp. 635-648.
42. Weinland, D., Ronfard, R., Boyer, E., 2011. A survey of vision-based methods for action representation, segmentation and recognition. Computer Vision Image Understanding 115, 224-241.
43. Wu, C., Khalili, A.H., Aghajan, H., 2010a. Multiview activity recognition in smart homes with spatio-temporal features. In: Proc. of the Fourth ACM/IEEE Internat. Conf. on Distributed Smart Cameras, ACM, New York, NY, USA, pp. 142-149.
44. Wu, X., Shi, Z., Zhong, Y., 2010b. Detailed analysis and evaluation of keypoint extraction methods. In: Internat. Conf. on Computer Application and System Modeling (ICCASM), pp. V2-562-V2-566.
45. Wu, X., Xu, D., Duan, L., Luo, J., 2011. Action recognition using context and appearance distribution features. In: IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 489-496.