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Definition
View- and rate-invariant human action recognition is the recognition of actions independent of the camera viewpoint, action speed, and frame rate of capture of the video.
Background
At its essence, human action is the movement of the body through a sequence of poses. The visual appearance of a given action in a video sequence depends upon several classes of variables: (1) the geometry of the person performing the action, (2) the style of the action being performed, (3) the clothing worn by the person, (4) the camera viewpoint, and (5) the time taken, not only for the entire action but also for each individual pose transition to complete. A generally applicable human action recognition system needs the ability to classify an action from its visual appearance regardless of the values of the above classes of variables. In other words, the system needs to be subject invariant, style invariant, clothing invariant, view...
References
Jiang H (2011) Human pose estimation using consistent max-covering. Pattern Anal Mach Intell IEEE Trans PP(99):1
Rosales R, Sclaroff S (2000) Inferring body pose without tracking body parts. In: Proceedings of the 2000 IEEE conference on computer vision and pattern recognition (CVPR), Hilton Head, vol 2, pp 721–727
Cao Z, Hidalgo G, Simon T, Wei SE, Sheikh Y (2018) OpenPose: realtime multi-person 2D pose estimation using Part Affinity Fields. arXiv preprint arXiv:1812.08008
Rao C, Yilmaz A, Shah M (2002) View-invariant representation and recognition of actions. Int J Comput Vis 50(2):203–226
Parameswaran V, Chellappa R (2005) Human action recognition using mutual invariants. Comput Vis Image Underst J 98(2):294–324
Parameswaran V, Chellappa R (2006) View invariance for human action recognition. Int J Comput Vis 66(1):83–101
Shen YP, Foroosh H (2009) View-invariant action recognition from point triplets. IEEE Trans Pattern Anal Mach Intell 31(10):1898–1905
Rahmani H, Mian A (2015) Learning a non-linear knowledge transfer model for cross-view action recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2458–2466
Ogale A, Karapurkar A, Aloimonos Y (2007) View-invariant modeling and recognition of human actions using grammars. In: Vidal R, Heyden A, Ma Yi (eds) Dynamical vision. Volume 4358 of lecture notes in computer science. Springer, Berlin/Heidelberg, pp 115–126
Weinland D, Boyer E, Ronfard R (2007) Action recognition from arbitrary views using 3D exemplars. In: Proceeding of the IEEE 11th international conference on computer vision, ICCV 2007, Rio de Janeiro, 14–21 Oct 2007, pp 1, 7
Souvenir R, Parrigan K (2009) Viewpoint manifolds for action recognition. EURASIP J Image Video Process
Gupta A, Martinez J, Little JJ, Woodham RJ (2014) 3D pose from motion for cross-view action recognition via non-linear circulant temporal encoding. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2601–2608
Junejo IN, Dexter E, Laptev I, Perez P (2011) View-independent action recognition from temporal self-similarities. IEEE Trans Pattern Anal Mach Intell 33(1):172–185
Seitz SM, Dyer CR (1997) View-invariant analysis of cyclic motion. Int J Comput Vis 25:231–251
Weinland D, Ronfard R, Boyer E (2006) Free viewpoint action recognition using motion history volumes. Comput Vis Image Underst 104(2–3):249–257
Veeraraghavan A, Srivastava A, Roy-Chowdhury AK, Chellappa R (2009) Rate-invariant recognition of humans and their activities. Image Process IEEE Trans 18(6):1326–1339
Bobick A, Tanawongsuwan R (2003) Performance analysis of time-distance gait parameters under different speeds. In: Proceedings of the 4th international conference on IEEE conference on computer vision and pattern recognition (CVPR), Madison
Veeraraghavan A, Chellappa R, Roy-Chowdhury AK (2006) The function space of an activity. In: Proceedings of the 2006 IEEE computer society conference on computer vision and pattern recognition (CVPR), New York, vol 1, pp 959–968
Rabiner L, Juang B (1993) Fundamentals of speech recognition. Prentice Hall, Englewood Cliffs. http://www.amazon.com/Fundamentals-Speech-Recognition-Lawrence-Rabiner/?dp/?0130151572
Maurel P, Sapiro G Dynamic shapes average. www.ima.umn.edu/preprints/may2003/1924.pdf
Ratanamahatana CA, Keogh E (2004) Making time-series classification more accurate using learned constraints. In: Proceedings of the SIAM international conference on data mining, Orlando, pp 11–22
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Parameswaran, V., Veeraraghavan, A. (2021). View- and Rate-Invariant Human Action Recognition. In: Computer Vision. Springer, Cham. https://doi.org/10.1007/978-3-030-03243-2_777-1
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