High-level event recognition in unconstrained videos

International Journal of Multimedia Information Retrieval

Volumn 2, Issue 2, 2013, Pages 73-101

  Jiang, Yu Gang ^a   Bhattacharya, Subhabrata ^b   Chang, Shih Fu ^c   Shah, Mubarak ^b  

^a FUDAN UNIVERSITY   (China)

^b UNIVERSITY OF CENTRAL FLORIDA   (United States)

^c Columbia University ^*  (United States)

Author keywords

Fusion; Multimedia event detection; Multimodal features; Recognition; Unconstrained videos; Video events

Indexed keywords

EID: 84986185450     PISSN: 21926611     EISSN: 2192662X     Source Type: Journal    
DOI: 10.1007/s13735-012-0024-2     Document Type: Article

References (174)

1. Aggarwal JK, Ryoo MS (2011) Human activity analysis: a review. ACM Comput Surv 43(3):1–16
2. Ali S, Shah M (2010) Human action recognition in videos using kinematic features and multiple instance learning. IEEE Trans Pattern Anal Mach Intell 32(2):288–303
3. Allen JF (1983) Maintaining knowledge about temporal intervals. Commun ACM 26(11):832–843
4. Atkeson CG, Hollerbach JM (1985) Kinematic features of unrestrained vertical arm movements. J Neurosci 5(9):2318–2330
5. Aucouturier JJ, Defreville B, Pachet F (2007) The bag-of-frames approach to audio pattern recognition: a sufficient model for urban soundscapes but not for polyphonic music. J Acoust Soc Am 122(2):881–891
6. Aytar Y, Shah M, Luo J (2008) Utilizing semantic word similarity measures for video retrieval. In: Proceedings of IEEE conference on computer vision and pattern recognition, Providence, USA
7. Baillie M, Jose JM (2003) Audio-based event detection for sports video. In: Proceedings of international conference on image and video retrieval, Urbana-Champaign, IL
8. Ballan L, Bertini M, Bimbo AD, Seidenari L, Serra G (2011) Event detection and recognition for semantic annotation of video. Multimedia Tools Appl 51(1):279–302
9. Banko M, Mittal VO, Witbrock, MJ (2000) Headline generation based on statistical translation. In: Proceedings of the annual meeting of the association for computational linguistics, Hong Kong
10. Bao L, Yu SI, Lan ZZ, Overwijk A, Jin Q, Langner B, Garbus M, Burger S, Metze F, Hauptmann A (2011) Informedia @ TRECVID 2011. In: Proceedings of NIST TRECVID, Workshop, Gaithersburg, MD, USA
11. Barbu, A., Bridge, A., Coroian, D., Dickinson, S., Mussman, S., Narayanaswamy, S., Salvi, D., Schmidt, L., Shangguan, J., Siskind, J.M., Waggoner, J., Wang, S., Wei, J., Yin, Y., Zhang, Z.: Large-scale automatic labeling of video events with verbs based on event-participant interaction. In: arXiv:1204.3616v1 (2012)
12. Bay H, Ess A, Tuytelaars T, van Gool L (2008) SURF: speeded up robust features. Comput Vision Image Underst 110(3):346–359
13. Beal MJ, Jojic N, Attias H (2003) A graphical model for audiovisual object tracking. IEEE Trans Pattern Anal Mach Intell 25(7):828–836
14. Blank M, Gorelick L, Shechtman E, Irani M, Basri R (2005) Actions as space-time shapes. In: Proceedings of International Conference on Computer Vision
15. Bobick AF (1997) Movement, activity, and action: the role of knowledge in the perception of motion. Philos Trans Royal Soc London 352:1257–1265
16. Boiman O, Shechtman E, Irani M (2008) In defense of nearest-neighbor based image classification. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
17. Brezeale D, Cook D (2008) Automatic video classification: a survey of the literature. IEEE Trans Syst Man Cybernet Part C 38(3):416–430
18. de Campos C, Ji Q (2011) Efficient structure learning of bayesian networks using constraints. J Mach Learn Res 12(3):663–689
19. Cao J, Zhang YD, Song YC, Chen ZN, Zhang X, Li JT (2009) MCG-WEBV: a benchmark dataset for web video analysis. Tech. rep., ICT-MCG-09-001, Institute of Computing Technology, Chinese Academy of Sciences
20. Castel C, Chaudron L, Tessier C (1996) What is going on? a high level interpretation of sequences of images. In: Proceedings of European conference on computer vision, Springer-Verlag, London, UK
21. Chang SF, He J, Jiang YG, El Khoury E, Ngo CW, Yanagawa A, Zavesky, E. (2008) Columbia University/VIREO-CityU/IRIT TRECVID2008 high-level feature extraction and interactive video search. In: Proceedings of NIST TRECVID, Workshop, Gaithersburg
22. Chang YL, Zeng W, Kamel I, Alonso R (1996) Integrated image and speech analysis for content-based video indexing. In: Proceedings of IEEE international conference on multimedia computing and systems, Washington, DC
23. Chen M, Xu ZE, Weinberger KQ, Sha F (2012) Marginalized stacked denoising autoencoders for domain adaptation. In: Proceedings international conference on machine learning
24. Cheng H et al (2011) Team SRI-Sarnoff’s AURORA System @ TRECVID 2011. In: Proceedings of NIST TRECVID, Workshop
25. Connolly CI (2007) Learning to recognize complex actions using conditional random fields. In: Proceedings of International Conference on Advances in Visual Computing
26. Cotton CV, Ellis DPW, Loui AC (2011) Soundtrack classification by transient events. In: Proceedings of IEEE international conference acoustics, speech, signal processing, pp 473–476
27. Dalal N, Triggs B (2005) Histogram of oriented gradients for human detection. In: Proceedings of IEEE conference on computer vision and pattern recognition
28. Deng J, Dong W, Socher R, Li LJ, Li K, Fei-Fei L (2009) Imagenet: a large-scale hierarchical image database. In: Proceedings of IEEE conference on computer vision and, pattern recognition
29. Dollar P, Rabaud V, Cottrell G, Belongie S (2005) Behavior recognition via sparse spatio-temporal features. In Proceedings of joint IEEE international workshop on visual surveillance and performance evaluation of tracking and surveillance
30. Dorko G (2012) Interest point detectors local descriptors. http://lear.inrialpes.fr/people/dorko/downloads.html
31. Duan L, Xu D, Tsang IW, Luo J (2010) Visual event recognition in videos by learning from web data. In: Proceedings of IEEE conference on computer vision and, pattern recognition
32. Duchenne O, Laptev I, Sivic J, Bach F, Ponce J (2009) Automatic annotation of human actions in video. In: Proceedings of IEEE international conference on computer vision
33. Eronen A, Peltonen V, Tuomi J, Klapuri A, Fagerlund S, Sorsa T, Lorho G, Huopaniemi J (2006) Audio-based context recognition. IEEE Trans Audio Speech Lang Process 14(1):321–329
34. Everingham M, van Gool L, Williams CKI, Winn J, Zisserman A (2007) The PASCAL visual object classes challenge 2007 (VOC2007) Results. http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2007/ results/index.shtml
35. Felzenszwalb P, Girshick R, McAllester D, Ramanan D (2010) Object detection with discriminatively trained part based models. IEEE Trans Pattern Anal Mach Intell 32(9):1530–1535
36. Feng Y, Lapata M (2010) How many words is a picture worth? automatic caption generation for news images. In: Proceedings of the annual meeting of the association for computational linguistics
37. Fillmore CJ (1968) The case for case. In: Bach E, Harms R (eds), Universals in Linguistic Theory, New York, pp 1–88
38. Fiscus J et al (2011) TRECVID multimedia event detection evaluation plan. http://www.nist.gov/itl/iad/mig/upload/MED11-EvalPlan-V03-20110801a.pdf
39. Francois ARJ, Nevatia R, Hobbs J, Bolles RC (2005) Verl: an ontology framework for representing and annotating video events. IEEE Multimedia Magazine 12(4):76–86
40. Frey BJ, Jojic N (2005) A comparison of algorithms for inference and learning in probabilistic graphical models. IEEE Trans Pattern Anal Mach Intell 27(9):1392–1416
41. van Gemert JC, Veenman CJ, Smeulders AWM, Geusebroek JM (2010) Visual word ambiguity. IEEE Trans Pattern Anal Mach Intell 32(7):1271–1283
42. Ghanem N, DeMenthon D, Doermann D, Davis L (2004) Representation and recognition of events in surveillance video using petri nets. In: Proceedings of IEEE conference on computer vision and pattern recognition workshop
43. Granger C (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37(3):424–438
44. Hakeem A, Sheikh Y, Shah M (2004) Casee: a hierarchical event representation for the analysis of videos. In: Proceedings of AAAI conference
45. Herbrich R (2001) Learning Kernel classifiers: theory and algorithms. The MIT Press, Cambridge
46. Hu Y, Cao L, Lv F, Yan S, Gong Y, Huang TS (2009) Action detection in complex scenes with spatial and temporal ambiguities. In: Proceedings of IEEE international conference on computer vision
47. Huang CL, Shih HC, Chao CY (2006) Semantic analysis of soccer video using dynamic bayesian network. IEEE Trans Multimedia 8(4):749–760
48. Inoue N, Kamishima Y, Wada T, Shinoda K, Sato S (2011) TokyoTech+Canon at TRECVID 2011. In: Proceedings of NIST TRECVID Workshop
49. Intille SS, Bobick AF (2001) Recognizing planned, multiperson action. Comput Vision Image Underst 81(3):414–445
50. Ivanov YA, Bobick AF (2000) Recognition of visual activities and interactions by stochastic parsing. IEEE Trans Pattern Anal Mach Intell 22(8):852–872
51. Jiang W, Cotton C, Chang SF, Ellis D, Loui AC (2009) Short-term audio-visual atoms for generic video concept classification. In: Proceedings of ACM international conference on multimedia
52. Jiang W, Loui AC (2011) Audio-visual grouplet: Temporal audio-visual interactions for general video concept classification. In: Proceedings of ACM international conference on multimedia
53. Jiang YG (2012) SUPER: Towards real-time event recognition in Internet videos. In: Proceedings of ACM international conference on multimedia retrieval
54. Jiang YG, Dai Q, Xue X, Liu W, Ngo CW (2012) Trajectory-based modeling of human actions with motion reference points. In: Proceedings of European conference on computer vision
55. Jiang YG, Ngo CW, Yang J (2007) Towards optimal bag-of-features for object categorization and semantic video retrieval. In: Proceedings of ACM international conference on image and video retrieval
56. Jiang YG, Yang J, Ngo CW, Hauptmann AG (2010) Representations of keypoint-based semantic concept detection: a comprehensive study. IEEE Trans Multimedia 12(1):42–53
57. Jiang YG, Ye G, Chang SF, Ellis D, Loui AC (2011) Consumer video understanding: a bechmark database and an evaluation of human and machine performance. In: Proceedings of ACM international conference on multimedia retrieval
58. Jiang YG, Zeng X, Ye G, Bhattacharya S, Ellis D, Shah M, Chang SF (2010) Columbia-UCF TRECVID2010 multimedia event detection: Combining multiple modalities, contextual concepts, and temporal matching. In: Proceedings of NIST TRECVID, Workshop
59. Joo SW, Chellappa R (2006) Attribute grammar-based event recognition and anomaly detection. In: Proceedings of IEEE conference on computer vision and pattern recognition, Workshop
60. Ke Y, Sukthankar R (2004) PCA-SIFT: a more distinctive representation for local image descriptors. In: Proceedings of IEEE conference on computer vision and pattern recognition
61. Klaser A, Marszalek M, Schmid C (2008) A spatio-temporal descriptor based on 3d-gradients. In: Proceedings of British machine vision conference
62. Knopp J, Prasad M, Willems G, Timofte R, van Gool L (2010) Hough transform and 3D SURF for robust three dimensional classification. In: Proceedings of European conference on computer vision
63. Kojima A, Tamura T, Fukunaga K (2002) Natural language description of human activities from video images based on concept hierarchy of actions. Int J Comput Vision 50(2):171–184
64. Kuehne H, Jhuang H, Garrote E, Poggio T, Serre T (2011) HMDB: a large video database for human motion recognition. In: Proceedings of IEEE international conference on computer vision
65. Laptev I (2005) On space-time interest points. Int J Comput Vision 64:107–123
66. Laptev I, Marszalek M, Schmid C, Rozenfeld B (2008) Learning realistic human actions from movies. In: Proceedings of IEEE conference on computer vision and pattern recognition
67. Lavee G, Rivlin E, Rudzsky M (2009) Understanding video events: a survey of methods for automatic interpretation of semantic occurrences in videos. IEEE Trans Syst Man Cybernet Part C 39(5):489–504
68. Lazebnik S, Schmid C, Ponce J (2006) Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. In: Proceedings of IEEE conference on computer vision and pattern recognition
69. Le QV, Zou WY, Yeung SY, Ng AY (2011) Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis. In: Proceedings of IEEE conference on computer vision and, pattern recognition
70. Lee K, Ellis DPW (2010) Audio-based semantic concept classification for consumer video. IEEE Trans Audio Speech Lang Process 18(6):1406–1416
71. Li W, Zhang Z, Liu Z (2008) Expandable data-driven graphical modeling of human actions based on salient postures. IEEE Trans Circ Syst Video Technol 18(11):1499–1510
72. Lindeberg T (1998) Feature detection with automatic scale selection. Int J Comput Vision 30:79–116
73. Liu J, Kuipers B, Savarese S (2011) Recognizing human actions by attributes. In: Proceedings of IEEE conference on computer vision and, pattern recognition, pp 3337–3344
74. Liu J, Luo J, Shah M (2009) Recognizing realistic actions from videos “in the wild”. In: Proceedings of IEEE conference on computer vision and pattern recognition
75. Liu J, Shah M (2008) Learning human actions via information maximization. In: Proceedings of IEEE conference on computer vision and pattern recognition
76. Loui AC, Luo J, Chang SF, Ellis D, Jiang W, Kennedy L, Lee K, Yanagawa A (2007) Kodak’s consumer video benchmark data set: concept definition and annotation. In: Proceedings of ACM international workshop on multimedia, information retrieval
77. Lowe D (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vision 60:91–110
78. Lu L, Hanjalic A (2008) Audio keywords discovery for text-like audio content analysis and retrieval. IEEE Trans Multimedia 10(1):74–85
79. Lucas BD, Kanade T (1981) An iterative image registration technique with an application to stereo vision. In: Proceedings of international joint conference on artificial intelligence
80. Lyon RF, Rehn M, Bengio S, Walters TC, Chechik G (2010) Sound retrieval and ranking using sparse auditory representations. Neural Comput 22(9):2390–2416
81. Maji S, Berg AC, Malik J (2008) Classification using intersection kernel support vector machines is efficient. In: Proceedings of IEEE conference on computer vision and pattern recognition
82. Mandel MI, Ellis DPW (2005) Song-level features and support vector machines for music classification. In: Proceedings of international society of music information retrieval conference
83. Manjunath BS, Ma WY (1996) Texture features for browsing and retrieval of image data. IEEE Trans Pattern Anal Mach Intell 18(8):837–842
84. Martin A, Doddington G, Kamm T, Ordowski M, Przybocki M (1997) The det curve in assessment of detection task performance. In: Procedings of European conference on speech communication and technology, pp 1895–1898
85. Matas J, Chum O, Urban M, Pajdla T (2002) Robust wide baseline stereo from maximally stable extremal regions. In: Proceedings of British machine vision conference, vol 1, pp 384–393
86. MediaEval: Multimedia retrieval benchmark evaluation. http://www.multimediaeval.org
87. Messing R, Pal C, Kautz H (2009) Activity recognition using the velocity histories of tracked keypoints. In: Proceedings of IEEE international conference on computer vision
88. Mikolajczyk K, Schmid C (2004) Scale and affine invariant interest point detectors. Int J Comput Vision 60:63–86
89. Mikolajczyk K, Schmid C (2005) A performance evaluation of local descriptors. IEEE Trans Pattern Anal Mach Intell 27(10):1615–1630
90. Mikolajczyk K, Tuytelaars T, Schmid C, Zisserman A, Matas J et al (2005) A comparison of affine region detectors. Int J Comput Vision 65(1/2):43–72
91. Minami K, Akutsu A, Hamada H, Tonomura Y (1998) Video handling with music and speech detection. IEEE Multimedia Magazine 5:17–25
92. Moore D, Essa I (2001) Recognizing multitasked activities using stochastic context-free grammar. In: Proceedings of AAAI conference
93. Moosmann F, Nowak E, Jurie F (2008) Randomized clustering forests for image classification. IEEE Trans Pattern Anal Mach Intell 30(9):1632–1646
94. Morsillo N, Mann G, Pal C (2010) Youtube scale, large vocabulary video annotation, Chapter 14 in video search and mining. Springer-Verlag series on studies in computational intelligence. Springer, Berlin, pp 357–386
95. Naphade M, Smith J, Tesic J, Chang SF, Hsu W, Kennedy L, Hauptmann A, Curtis J (2006) Large-scale concept ontology for multimedia. IEEE Multimedia Magazine 13(3):86–91
96. Natarajan P et al (2011) BBN VISER TRECVID 2011 multimedia event detection system. In: Proceedings of NIST TRECVID, Workshop
97. Natarajan P, Nevatia R (2008) Online, real-time tracking and recognition of human actions. In: Proceedings of IEEE workshop on motion and video, computing, pp 1–8
98. Natsev A, Smith JR, Hill M, Hua G, Huang B, Merler M, Xie L, Ouyang H, Zhou, M (2010) IBM Research TRECVID-2010 video copy detection and multimedia event detection system. In: Proceedings of NIST TRECVID, Workshop
99. NIST Trecvid Multimedia Event Detection (MED) task. http://www.nist.gov/itl/iad/mig/med.cfm
100. Nister D, Stewenius H (2006) Scalable recognition with a vocabulary tree. In: Proceedings of IEEE conference on computer vision and pattern recognition
101. Nowak E, Jurie F, Triggs B (2006) Sampling strategies for bag-of-features image classification. In: Proceedings of European conference on computer vision
102. Oikonomopoulos A, Patras I, Pantic M (2011) Spatiotemporal localization and categorization of human actions in unsegmented image sequences. IEEE Trans Image Process 20(4):1126–1140
103. Ojala T, Pietikainen M, Maenpaa T (2002) Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans Pattern Anal Mach Intell 24(7):971–987
104. Oliva A, Torralba A (2001) Modeling the shape of the scene: a holistic representation of the spatial envelope. Int J Comput Vision 42:145–175
105. Ordonez V, Kulkarni G, Berg TL (2011) Im2Text: describing images using 1 million captioned photographs. In: Proceedings of advances in neural information processing systems
106. Papineni K, Roukos S, Ward T, Zhu WJ (2002) Bleu: a method for automatic evaluation of machine translation. In: Proceeedings of the annual meeting of the association for computational linguistics
107. Patterson RD, Robinson K, Holdsworth J, McKeown D, Zhang C, Allerhand M (1992) Complex sounds and auditory images. In: Proceedings of international symposium on hearing, pp 429–446
108. Perronnin F, Sanchez J, Mensink T (2010) Improving the fisher kernel for large-scale image classification. In: Proceedings of European conference on computer vision
109. Philbin J, Chum O, Isard M, Sivic J, Zisserman A (2008) Lost in quantization: improving particular object retrieval in large scale image databases. In: Proceedings of IEEE conference on computer vision and pattern recognition
110. Pollard C, Sag I (1994) Head-driven phrase structure grammar. Chicago University Press, Chicago
111. Poppe R (2010) Survey on vision-based human action recognition. Image Vision Comput 28(6):976–990
112. Rapantzikos K, Avrithis Y, Kollias S (2009) Dense saliency- based spatiotemporal feature points for action recognition. In: Proceedings of IEEE conference on computer vision and pattern recognition
113. Raptis M, Soatto S (2010) Tracklet descriptors for action modeling and video analysis. In: Proceedings of European conference on computer vision
114. Rodriguez MD, Ahmed J, Shah M (2008) Action mach: a spatio-temporal maximum average correlation height filter for action recognition. In: Procedings of IEEE conference on computer vision and pattern recognition
115. Rubner Y, Tomasi C, Guibas LJ (2000) The earth mover’s distance as a metric for image retrieval. Int J Comput Vision 40(2):99– 121
116. Russell B, Torralba A, Murphy K, Freeman WT (2008) LabelMe: a database and web-based tool for image annotation. Int J Comput Vision 77(1–3):157–173
117. Ryoo MS, Aggarwal JK (2006) Recognition of composite human activities through context-free grammar based representation. In: Proceedings pf IEEE conference on computer vision and pattern recognition
118. Sadlier DA, O’Connor NE (2005) Event detection in field sports video using audio-visual features and a support vector machine. IEEE Trans Circ Syst Video Technol 15(10):1225–1233
119. van de Sande KEA, Gevers T, Snoek CGM (2010) Evaluating color descriptors for object and scene recognition. IEEE Trans Pattern Anal Mach Intell 32(9):1582–1596
120. Satkin S, Hebert M (2010) Modeling the temporal extent of actions. In: Proceedings of European conference on computer vision
121. Schuldt C, Laptev I, Caputo B (2004) Recognizing human actions: a local SVM approach. In: Proceedings of international conference on pattern recognition
122. Scovanner P, Ali S, Shah M (2007) A 3-dimensional SIFT descriptor and its application to action recognition. In: Proceedings of ACM international conference on multimedia
123. Shechtman E, Irani M (2007) Matching local self-similarities across images and videos. In: Proceedings lo IEEE conference on computer vision and pattern recognition
124. Shotton J, Johnson M, Cipolla R (2008) Semantic texton forests for image categorization and segmentation. In: Proceedings of IEEE conference on computer vision and pattern recognitio
125. Si Z, Pei M, Yao B, Zhu SC (2011) Unsupervised learning of event and-or grammar and semantics from video. In: Proceedings IEEE international conference on computer vision
126. Silpa-Anan C, Hartley R (2008) Optimised KD-trees for fast image descriptor matching. In: IEEE conference on computer vision and pattern recognition
127. Sivic J, Zisserman A (2003) Video Google: a text retrieval approach to object matching in videos. In: Proceedings of IEEE international conference on computer vision
128. Smeaton AF, Over P, Kraaij W (2006) Evaluation campaigns and TRECVid. In: Proceedings of ACM international workshop on multimedia information retrieval
129. Smeulders AWM, Worring M, Santini S, Gupta A, Jain R (2000) Content based image retrieval at the end of the early years. IEEE Trans Pattern Anal Mach Intell 22(12):1349–1380
130. Snoek CGM, Worring M (2008) Concept-based video retrieval. Found Trends Inf Retr 2(4):215–322
131. Starner TE (1995) Visual recognition of american sign language using hidden markov models. Ph.D. thesis
132. Sun J, Wu X, Yan S, Cheong LF, Chua TS, Li J (2009) Hierarchical spatio-temporal context modeling for action recognition. In: Proceedings of IEEE conference on computer vision and pattern recognition
133. Sun SW, Wang YCF, Hung YL, Chang CL, Chen KC, Cheng SS, Wang HM, Liao HYM (2011) Automatic annotation of web videos. In: Proceedings of IEEE international conference on multimedia and expo
134. Tan CC, Jiang YG, Ngo CW (2011) Towards textually describing complex video contents with audio-visual concept classifiers. In: Proceedings of ACM international conference on multimedia
135. Taylor G, Fergus R, LeCun Y, Bregler C (2010) Convolutional learning of spatio-temporal features. In: Proceedings of European conference on computer vision
136. Torresani L, Szummer M, Fitzgibbon A (2010) Efficient object category recognition using classemes. In: Proceedings of European conference on computer vision
137. Tran SD, Davis LS (2008) Event modeling and recognition using markov logic networks. In: Proceedings of European conference on computer vision
138. Tsekeridou S, Pitas I (2001) Content-based video parsing and indexing based on audio-visual interaction. IEEE Transactions on Circuits and Systems for Video Technology 11(4):522–535
139. Turaga P, Chellappa R, Subrahmanian VS, Udrea O (2008) Machine recognition of human activities: a survey. IEEE Trans Circ Syst Video Technol 18(11):1473–1488
140. Tuytelaars T (2010) Dense interest points. In: Proceedings of IEEE conference on computer vision and pattern recognition, pp 2281–2288
141. Uemura H, Ishikawa S, Mikolajczyk K (2008) Feature tracking and motion compensation for action recognition. In: Proceedings British machine vision conference
142. Uijlings JRR, Smeulders AWM, Scha RJH (2010) Real-time visual concept classification. IEEE Trans Multimedia 12(7): 665–680
143. University of Central Florida 50 human action dataset (2010). http://server.cs.ucf.edu/~ision/data/UCF50.rar
144. Vail DL, Veloso MM, Lafferty JD (2007) Conditional random fields for activity recognition. In: Proceedings of international joint conference on autonomous agents and multiagent systems
145. Vedaldi A, Gulshan V, Varma M, Zisserman A (2009) Multiple kernels for object detection. In: Proceedings of IEEE international conference on computer vision
146. Vincent P, Larochelle H, Bengio Y, Manzagol PA (2008) Extracting and composing robust features with denoising autoencoders. In: Procedings of international conference on machine learning
147. Vincent P, Larochelle H, Lajoie I, Bengio Y, Manzagol PA (2010) Stacked denoising autoencoders: learning useful representations in a deep network with a local denoising criterion. J Mach Learn Res 11(12):3371–3408
148. Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. In; Proceedings of IEEE conference on computer vision and pattern recognition
149. Wang F, Jiang YG, Ngo CW (2008) Video event detection using motion relativity and visual relatedness. In: Proceedings of ACM international conference on multimedia
150. Wang H, Klaser A, Schmid C, Liu CL (2011) Action recognition by dense trajectories. In: Proceedings of IEEE conference on computer vision and pattern recognition
151. Wang H, Ullah MM, Klaser A, Laptev I, Schmid C (2008) Evaluation of local spatio-temporal features for action recognition. In: Proceedings of British machine vision conference
152. Wang J, Kumar S, Chang SF (2010) Semi-supervised hashing for scalable image retrieval. In: Proceedings of IEEE conference on computer vision and pattern recognition
153. Wang L, Suter D (2007) Recognizing human activities from silhouettes: motion subspace and factorial discriminative graphical model. In: Proceedings of IEEE conference on computer vision and pattern recognition
154. Wang Y, Mori G (2009) Max-margin hidden conditional random fields for human action recognition. In: Proceedings of IEEE conference on computer vision and pattern recognition
155. Weinland D, Ronfard R, Boyer E (2006) Free viewpoint action recognition using motion history volumes. Comput Vision Image Underst 104(2):249–257
156. Weiss Y, Torralba A, Fergus R (2008) Spectral hashing. In: Proceedings of advances in neural information processing systems
157. White B, Yeh T, Lin J, Davis L (2009) Web-scale computer vision using mapreduce for multimedia data mining. In: Proceedings of ACM SIGKDD workshop on multimedia data mining
158. Willems G, Tuytelaars T, van Gool L (2008) An efficient dense and scale-invariant spatio-temporal interest point detector. In: Proceedings European conference on computer vision
159. Wu S, Oreifej O, Shah M (2011) Action recognition in videos acquired by a moving camera using motion decomposition of lagrangian particle trajectories. In: Proceedings of IEEE international conference on computer vision
160. Xie L, Xu P, Chang SF, Divakaran A, Sun H (2004) Structure analysis of soccer video with domain knowledge and hidden markov models. Pattern Recognit Lett 25(7):767–775
161. Xu C, Wang J, Lu H, Zhang Y (2008) A novel framework for semantic annotation and personalized retrieval of sports video. IEEE Trans Multimedia 10(3):421–436
162. Xu D, Chang SF (2008) Video event recognition using Kernel methods with multilevel temporal alignment. IEEE Trans Pattern Anal Mach Intell 30(11):1985–1997
163. Xu M, Maddage NC, Xu C, Kankanhalli M, Tian Q (2003) Creating audio keywords for event detection in soccer video. In: Proceedings IEEE international conference on multimedia and expo
164. Yamato J, Ohya J, Ishii K (1992) Recognizing human action in time-sequential images using hidden markov model. In: Proceedings of IEEE conference on computer vision and pattern recognition
165. Yan R, Fleury MO, Merler M, Natsev A, Smith JR (2009) Large-scale multimedia semantic concept modeling using robust subspace bagging and mapreduce. In: Proceedings of ACM workshop on large-scale multimedia retrieval and mining
166. Yanagawa A, Hsu W, Chang SF (2006) Brief descriptions of visual features for baseline trecvid concept detectors. Columbia University, Tech. rep.
167. Yao B, Yang X, Lin L, Lee M, Zhu S (2010) I2T: Image parsing to text description. Proc IEEE 98(8):1485–1508
168. Ye G, Jhuo IH, Liu D, Jiang YG, Chang SF (2012) Joint audio-visual bi-modal codewords for video event detection. In: Proceedings of ACM international conference on multimedia retrieval
169. Ye G, Liu D, Jhuo IH, Chang SF (2012) Robust late fusion with rank minimization. In: Proceedings IEEE conference on computer vision and pattern recognition
170. Yu TH, Kim TK, Cipolla R (2010) Real-time action recognition by sptiotemoral semantic and structural forests. In: Proceedings of British machine vision conference
171. Yuan F, Prinet V, Yuan J (2010) Middle-level representation for human activities recognition: the role of spatio-temporal relationships. In: Proceedings of ECCV Workshop on human motion: understanding, modeling, capture and animation
172. Yuen J, Russell BC, Liu C, Torralba A (2009) LabelMe video: building a video database with human annotations. In: Proceedings of international conference on computer vision
173. Zhang D, Chang SF (2002) Event detection in baseball video using superimposed caption recognition. In: Proceedings of ACM international conference on multimedia
174. Zhang J, Marszalek M, Lazebnik S, Schmid C (2007) Local features and kernels for classification of texture and object categories: a comprehensive study. Int J Comput Vision 73(2):213–238