id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_3f4o5vkwirca5doewxivlid55u	Bhaskar Chakraborty	Human action recognition using an ensemble of body-part detectors	2011	23	.pdf	application/pdf	6289	716	68	HMMs to model the stochastic movement of the body-parts for action recognition. Actions like walking, jogging, running, boxing and waving are systematic combinations of the motion of different human body components. Figure 1: The proposed framework for action recognition based on probabilistic optimization model of body parts using Hidden Markov Models (a) Construction of body-part Features from body parts B are used to model the action likelihood Pr(a|B,I), and Several methods for learning and recognizing human actions directly from image measurements have been proposed in the literature (Black & Jepson 1996, Davis & Bobick 1997, Zelnik-Manor & Irani 2001, Chomat & Crowley 1999). Also (Mendoza & de la Blanca 2007), detect human actions using HMMs In our method we combine the advantages of full body and part-based action recognition approaches. Here, for each action ai one discrete HMM is constructed using features from the contributing body parts: Blegs or Barms. 'HMM-based Human Action Recognition Using Multiview Image Sequences'.	./cache/work_3f4o5vkwirca5doewxivlid55u.pdf	./txt/work_3f4o5vkwirca5doewxivlid55u.txt