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Probability-based Dynamic Time Warping and Bag-of-Visual-and-Depth-Words for Human Gesture Recognition in RGB-D
dc.contributor.author | Hernández-Vela, Antonio |
dc.contributor.author | Bautista, Miguel Angel |
dc.contributor.author | Perez Sala, Xavier |
dc.contributor.author | Ponce, Víctor |
dc.contributor.author | Escalera, Sergio |
dc.contributor.author | Baró, Xavier |
dc.contributor.author | Pujol, Oriol |
dc.contributor.author | Angulo Bahón, Cecilio |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2014-11-07T09:20:45Z |
dc.date.created | 2014-12 |
dc.date.issued | 2014-12 |
dc.identifier.citation | Hernández-Vela, A. [et al.]. Probability-based Dynamic Time Warping and Bag-of-Visual-and-Depth-Words for Human Gesture Recognition in RGB-D. "Pattern recognition letters", Desembre 2014, vol. 50, p. 112-121. |
dc.identifier.issn | 0167-8655 |
dc.identifier.uri | http://hdl.handle.net/2117/24589 |
dc.description.abstract | We present a methodology to address the problem of human gesture segmentation and recognition in video and depth image sequences. A Bag-of-Visual-and-Depth-Words (BoVDW) model is introduced as an extension of the Bag-of-Visual-Words (BoVW) model. State-of-the-art RGB and depth features, including a newly proposed depth descriptor, are analysed and combined in a late fusion form. The method is integrated in a Human Gesture Recognition pipeline, together with a novel probability-based Dynamic Time Warping (PDTW) algorithm which is used to perform prior segmentation of idle gestures. The proposed DTW variant uses samples of the same gesture category to build a Gaussian Mixture Model driven probabilistic model of that gesture class. Results of the whole Human Gesture Recognition pipeline in a public data set show better performance in comparison to both standard BoVW model and DTW approach. |
dc.format.extent | 10 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial |
dc.subject.lcsh | Computer vision |
dc.subject.lcsh | Pattern recognition systems |
dc.subject.other | RGB-D |
dc.subject.other | Bag-of-Words |
dc.subject.other | Dynamic Time Warping |
dc.subject.other | Human Gesture Recognition |
dc.title | Probability-based Dynamic Time Warping and Bag-of-Visual-and-Depth-Words for Human Gesture Recognition in RGB-D |
dc.type | Article |
dc.subject.lemac | Visió per ordinador |
dc.subject.lemac | Reconeixement de formes (Informàtica) |
dc.contributor.group | Universitat Politècnica de Catalunya. GREC - Grup de Recerca en Enginyeria del Coneixement |
dc.identifier.doi | 10.1016/j.patrec.2013.09.009 |
dc.relation.publisherversion | http://www.sciencedirect.com/science/article/pii/S0167865513003450 |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 15263213 |
dc.description.version | Postprint (published version) |
dc.date.lift | 10000-01-01 |
local.citation.author | Hernández-Vela, A.; Bautista, M.; Perez, X.; Ponce, V.; Escalera, S.; Xavier, B.; Pujol, O.; Angulo, C. |
local.citation.publicationName | Pattern recognition letters |
local.citation.volume | 50 |
local.citation.startingPage | 112 |
local.citation.endingPage | 121 |
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