eprintid: 10115642
rev_number: 17
eprint_status: archive
userid: 608
dir: disk0/10/11/56/42
datestamp: 2020-11-23 09:38:48
lastmod: 2021-11-04 00:15:27
status_changed: 2020-11-23 09:38:48
type: proceedings_section
metadata_visibility: show
creators_name: Bautista, MÁ
creators_name: Hernández-Vela, A
creators_name: Ponce, V
creators_name: Perez-Sala, X
creators_name: Baró, X
creators_name: Pujol, O
creators_name: Angulo, C
creators_name: Escalera, S
title: Probability-Based Dynamic Time Warping for Gesture Recognition on RGB-D Data
ispublished: pub
divisions: UCL
divisions: B04
divisions: C04
divisions: F34
keywords: Depth maps, Gesture Recognition, Dynamic Time Warping, Statistical Pattern Recognition
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: Dynamic Time Warping (DTW) is commonly used in gesture recognition tasks in order to tackle the temporal length variability of gestures. In the DTW framework, a set of gesture patterns are compared one by one to a maybe infinite test sequence, and a query gesture category is recognized if a warping cost below a certain threshold is found within the test sequence. Nevertheless, either taking one single sample per gesture category or a set of isolated samples may not encode the variability of such gesture category. In this paper, a probability-based DTW for gesture recognition is proposed. Different samples of the same gesture pattern obtained from RGB-Depth data are used to build a Gaussian-based probabilistic model of the gesture. Finally, the cost of DTW has been adapted accordingly to the new model. The proposed approach is tested in a challenging scenario, showing better performance of the probability-based DTW in comparison to state-of-the-art approaches for gesture recognition on RGB-D data.
date: 2013
date_type: published
publisher: Springer, Berlin, Heidelberg
official_url: https://doi.org/10.1007/978-3-642-40303-3_14
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1818991
doi: 10.1007/978-3-642-40303-3_14
isbn_13: 9783642403026
publication_declined: 2021-04-21T22:48:20BST
lyricists_name: Ponce Lopez, Victor
lyricists_id: VPONC48
actors_name: Jayawardana, Anusha
actors_id: AJAYA51
actors_role: owner
full_text_status: public
series: Lecture Notes in Computer Science book series
volume: 7854
pagerange: 126-135
event_title: International Workshop on Depth Image Analysis and Applications 2012
issn: 1611-3349
book_title: International Workshop on Depth Image Analysis and Applications WDIA 2012: Advances in Depth Image Analysis and Applications
citation:        Bautista, MÁ;    Hernández-Vela, A;    Ponce, V;    Perez-Sala, X;    Baró, X;    Pujol, O;    Angulo, C;           Bautista, MÁ;  Hernández-Vela, A;  Ponce, V;  Perez-Sala, X;  Baró, X;  Pujol, O;  Angulo, C;  Escalera, S;   - view fewer <#>    (2013)    Probability-Based Dynamic Time Warping for Gesture Recognition on RGB-D Data.                     In:  International Workshop on Depth Image Analysis and Applications WDIA 2012: Advances in Depth Image Analysis and Applications.  (pp. pp. 126-135).  Springer, Berlin, Heidelberg       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10115642/1/Ponce%20Lopez_PDTW_ICPRWorkshop.pdf