Human action recognition employing negative space features

Journal of Visual Communication and Image Representation

Volumn 24, Issue 3, 2013, Pages 217-231

  Rahman, Shah Atiqur ^a   Leung, M K H ^b   Cho, Siu Yeung ^c  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b UNIVERSITI TUNKU ABDUL RAHMAN   (Malaysia)

^c UNIVERSITY OF NOTTINGHAM NINGBO CHINA   (China)

Author keywords

Complex activity; Computer vision; Dynamic Time Warping; Fuzzy function; Human action recognition; Negative space; Region partitioning; Silhouette

Indexed keywords

COMPLEX ACTIVITY; DYNAMIC TIME WARPING; FUZZY FUNCTION; HUMAN-ACTION RECOGNITION; NEGATIVE SPACE; REGION PARTITIONING; SILHOUETTE;

COMPUTER VISION; FEATURE EXTRACTION; VIDEO RECORDING;

GESTURE RECOGNITION;

EID: 84873851175     PISSN: 10473203     EISSN: 10959076     Source Type: Journal    
DOI: 10.1016/j.jvcir.2012.12.001     Document Type: Article

References (64)

1. N. Ikizler, and D.A. Forsyth Searching for complex human activities with no visual examples Int. J. Comput. Vision 80 2008 337 357
2. R. Goldenberg, R. Kimmel, E. Rivlin, and M. Rudzsky Behavior classification by eigen decomposition of periodic motions Pattern Recogn. 38 2005 1033 1043 (Pubitemid 40537024)
3. A. Diaf, R. Ksantini, B. Boufama, R. Benlamri, A novel human motion recognition method based on eigenspace, Lect. Notes Comput. Sci. (2010) 167-175.
4. B. Wei, T. Dacheng, and R. Yong Cross-domain human action recognition IEEE Trans. Syst. Man Cybern. B Cybern. 42 2012 298 307
5. I. Saleemi, L. Hartung, M. Shah, Scene understanding by statistical modeling of motion patterns, Comput. Vis. Pattern Recogn. (2010) 2069-2076.
6. L. Wang, W. Hu, and T. Tan Recent developments in human motion analysis Pattern Recogn. 36 2003 585 601
7. S.A. Rahman, L. Li, M.K.H. Leung, Human action recognition by negative space analysis, Cyberworlds (CW) (2010) 354-359.
8. S.A. Rahman, S.-Y. Cho, M.K.H. Leung, Complex human activity searching in a video employing negative space analysis, in: International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV), Las Vegas, USA, 2011.
9. R. Poppe A survey on vision-based human action recognition Image Vis. Comput. 28 2010 976 990
10. T.B. Moeslund, A. Hilton, and V. Kruger A survey of advances in vision-based human motion capture and analysis Comput. Vis. Image Underst. 104 2006 90 126 (Pubitemid 44573873)
11. D. Weinland, R. Ronfard, and E. Boyer A survey of vision-based methods for action representation, segmentation and recognition Comput. Vis. Image Underst. 115 2011 224 241
12. L. Wang, and D. Suter Learning and matching of dynamic shape manifolds for human action recognition Image Process. 16 2007 1646 1661 (Pubitemid 46796060)
13. I. Laptev, T. Lindeberg, Space-time interest points, in: International Conference on Computer Vision, 2003, pp. 432-439.
14. P. Dollar, V. Rabaud, G. Cottrell, S. Belongie, Behavior recognition via sparse spatio-temporal features, Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, 2005, pp. 65-72. (Pubitemid 46178025)
15. J.C. Niebles, H. Wang, and L. Fei-Fei Unsupervised learning of human action categories using spatial-temporal words Int. J. Comput. Vision 79 2008 299 318
16. X. Wang, X. Ma, and W.E.L. Grimson Unsupervised activity perception in crowded and complicated scenes using hierarchical bayesian models IEEE Trans. Pattern Anal. Mach. Intell. 31 2009 539 555
17. J. Yuan, Z. Liu, Y. Wu, Discriminative subvolume search for efficient action detection, Computer Vis. Pattern Recogn. (2009) 2442-2449.
18. G. Willems, J.H. Becker, L.V. Gool, Exemplar-based action recognition in video, in: BMVC, 2009, pp. 1-11.
19. K. Rapantzikos, Y. Avrithis, S. Kollias, Dense saliency-based spatiotemporal feature points for action recognition, Comput. Vis. Pattern Recogn. (2009) 1454-1461.
20. A. Fathi, G. Mori, Action recognition by learning mid-level motion features, Comput. Vis. Pattern Recogn. (2008) 1-8.
21. A. Yao, J. Gall, L. Van Gool, A Hough transform-based voting framework for action recognition, Comput. Vis. Pattern Recogn. (2010) 2061-2068.
22. J. Gall, A. Yao, N. Razavi, L. Van Gool, and V. Lempitsky Hough forests for object detection, tracking, and action recognition IEEE Trans. Pattern Anal. Mach. Intell. 33 2011 2188 2202
23. R. Ji, X. Sun, H. Yao, P. Xu, T. Liu, Attention-driven action retrieval with DTW-based 3d descriptor matching, in: ACM International Conference on Multimedia, ACM, Vancouver, British Columbia, Canada, 2008, pp. 619-622.
24. R. Ji, H. Yao, and X. Sun Actor-independent action search using spatiotemporal vocabulary with appearance hashing Pattern Recogn. 44 2011 624 638
25. H. Seo, and P. Milanfar Action recognition from one example IEEE Trans. Pattern Anal. Mach. Intell. 33 2011 867 882
26. Y. Guo, G. Xu, S. Tsuji, Understanding human motion patterns, in: International Conference on Image Analysis and Pattern Recognition, 1994, pp. 325-329.
27. M.K.H. Leung, and Y.H. Yang First sight: a human body outline labeling system IEEE Trans. Pattern Anal. Mach. Intell. 17 1995 359 377
28. C.R. Wren, A. Azarbayejani, T. Darrell, and A.P. Pentland Pfinder: real-time tracking of the human body IEEE Trans. Pattern Anal. Mach. Intell. 19 1997 780 785 (Pubitemid 127762271)
29. P.F. Felzenszwalb, and D.P. Huttenlocher Pictorial structures for object recognition Int. J. Comput. Vision 61 2005 55 79
30. G.K.M. Cheung, K. Takeo, B. Jean-Yves, H. Mark, A real time system for robust 3D Voxel reconstruction of human motions, Comput. Vis. Pattern Recogn. (2000) 714-720.
31. M.W. Lee, and R. Nevatia Human pose tracking in monocular sequence using multilevel structured models IEEE Trans. Pattern Anal. Mach. Intell. 31 2009 27 38
32. Y. Shen, H. Foroosh, View-invariant action recognition using fundamental ratios, Comput. Vis. Pattern Recogn. (2008) 1-6.
33. I.N. Junejo, E. Dexter, I. Laptev, and P. Perez View-independent action recognition from temporal self-similarities IEEE Trans. Pattern Anal. Mach. Intell. 33 2011 172 185
34. P. Peursum, S. Venkatesh, G. West, Tracking-as-recognition for articulated full-body human motion analysis, Comput. Vis. Pattern Recogn. (2007) 1-8.
35. W. Li, Z. Zhang, Z. Liu, Graphical modeling and decoding of human actions, IEEE Workshop Multimedia Signal Process. (2008) 175-180.
36. A.F. Bobick, and J.W. Davis The recognition of human movement using temporal templates IEEE Trans. Pattern Anal. Mach. Intell. 23 2001 257 267 (Pubitemid 32286632)
37. H. Meng, N. Pears, C. Bailey, A human action recognition system for embedded computer vision application, Comput. Vis. Pattern Recogn. (2007) 1-6.
38. D. Weinland, R. Ronfard, and E. Boyer Free viewpoint action recognition using motion history volumes Comput. Vis. Image Underst. 104 2006 249 257 (Pubitemid 44573869)
39. J. Han, B. Bhanu, Human Activity recognition in thermal infrared imagery, Comput. Vis. Pattern Recogn. (2005) 17.
40. A. Roy, S. Sural, and J. Mukherjee Gait recognition using pose kinematics and pose energy image Signal Process. 92 2012 780 792
41. T.H.W. Lam, K.H. Cheung, and J.N.K. Liu Gait flow image: a silhouette-based gait representation for human identification Pattern Recogn. 44 2011 973 987
42. H.W. Lin, M.C. Hu, J.L. Wu, Gait-based action recognition via accelerated minimum incremental coding length classifier, Lecture Notes Comput. Sci. (2012) 266-276.
43. S. Kumar, B. Raman, N. Sukavanam, Human action recognition in a wide and complex environment, SPIE-The International Society for Optical Engineering, 2011.
44. L. Gorelick, M. Blank, E. Shechtman, M. Irani, and R. Basri Actions as space-time shapes IEEE Trans. Pattern Anal. Mach. Intell. 29 2007 2247 2253 (Pubitemid 350124072)
45. A. Yilmaz, M. Shah, Actions sketch: a novel action representation, Comput. Vis. Pattern Recogn. 981 (2005) 984-989. (Pubitemid 43897299)
46. W. Lin, M.-T. Sun, R. Poovandran, Z. Zhang, Human activity recognition for video surveillance, International Symp. Circuits Systems (2008) 2737-2740.
47. N. Ikizler, and P. Duygulu Histogram of oriented rectangles: a new pose descriptor for human action recognition Image Vis. Comput. 27 2009 1515 1526
48. J.W. Davis, and A. Tyagi Minimal-latency human action recognition using reliable-inference Image Vis. Comput. 24 2006 455 472 (Pubitemid 43782937)
49. L. Wang, D. Suter, Recognizing human activities from silhouettes: motion subspace and factorial discriminative graphical model, Comput. Vis. Pattern Recogn. (2007) 1-8.
50. F. Lv, R. Nevatia, Single View human action recognition using key pose matching and Viterbi path searching, Comput. Vis. Pattern Recogn. (2007) 1-8.
51. K. Jia, D.-Y. Yeung, Human action recognition using local spatio-temporal discriminant embedding, Comput. Vis. Pattern Recogn. (2008) 1-8.
52. M.F. Abdelkader, W. Abd-Almageed, A. Srivastava, and R. Chellappa Silhouette-based gesture and action recognition via modeling trajectories on Riemannian shape manifolds Comput. Vis. Image Underst. 115 2011 439 455
53. C. Chen, J. Liang, and X. Zhu Gait recognition based on improved dynamic Bayesian networks Pattern Recogn. 44 2011 988 995
54. X. Wu, Y. Jia, and W. Liang Incremental discriminant-analysis of canonical correlations for action recognition Pattern Recogn. 43 2010 4190 4197
55. L. Li, W. Huang, I.Y.-H. Gu, and T. Qi Statistical modeling of complex backgrounds for foreground object detection Image Process. 13 2004 1459 1472
56. M.R. Teague Image analysis via the general theory of moments J. Opt. Soc. Am. 70 1980 920 930
57. C. Schuldt, I. Laptev, B. Caputo, Recognizing human actions: a local SVM approach, in: International Conference on, Pattern Recognition, 2004, pp. 32-36.
58. M. Bregonzio, G. Shaogang, X. Tao, Recognizing action as clouds of space-time interest points, Comput. Vis. Pattern Recogn. (2009) 1948-1955.
59. M. Bregonzio, T. Xiang, and S. Gong Fusing appearance and distribution information of interest points for action recognition Pattern Recogn. 45 2012 1220 1234
60. V. Kellokumpu, G. Zhao, M. Pietikinen, Dynamic textures for human movement recognition, in: ACM International Conference on Image and Video Retrieval, ACM, Xi'an, China, 2010, pp. 470-476.
61. Z. Lin, Z. Jiang, L.S. Davis, Recognizing actions by shape-motion prototype trees, in: International Conference on Computer Vision, 2009, pp. 444-451.
62. K. Schindler, L. van Gool, Action snippets: how many frames does human action recognition require? Comput. Vis. Pattern Recogn. (2008) 1-8.
63. J. Liu, M. Shah, Learning human actions via information maximization, Comput. Vis. Pattern Recogn. (2008) 1-8.
64. M. Ahmad, and S.-W. Lee Human action recognition using shape and CLG-motion flow from multi-view image sequences Pattern Recogn. 41 2008 2237 2252