Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/119123
Title: | Probability-based Dynamic Time Warping and Bag-of-Visual-and-Depth-Words for Human Gesture Recognition in RGB-D |
Author: | Hernández-Vela, Antonio Bautista Martín, Miguel Ángel Perez-Sala, Xavier Ponce López, Víctor Escalera Guerrero, Sergio Baró i Solé, Xavier Pujol Vila, Oriol Angulo Bahón, Cecilio |
Keywords: | Algorismes computacionals Processos gaussians Computer algorithms Gaussian processes |
Issue Date: | 6-Sep-2014 |
Publisher: | Elsevier B.V. |
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. |
Note: | Versió postprint del document publicat a: https://doi.org/10.1016/j.patrec.2013.09.009 |
It is part of: | Pattern Recognition Letters, 2014, vol. 50, p. 112-121 |
URI: | http://hdl.handle.net/2445/119123 |
Related resource: | https://doi.org/10.1016/j.patrec.2013.09.009 |
ISSN: | 0167-8655 |
Appears in Collections: | Articles publicats en revistes (Matemàtiques i Informàtica) |
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