TY  - CONF
AU  - Miguel Angel Bautista
AU  - Antonio Hernandez
AU  - Victor Ponce
AU  - Xavier Perez Sala
AU  - Xavier Baro
AU  - Oriol Pujol
AU  - Cecilio Angulo
AU  - Sergio Escalera
A2  - WDIA
PY  - 2012//
TI  - Probability-based Dynamic TimeWarping for Gesture Recognition on RGB-D data
BT  - 21st International Conference on Pattern Recognition International Workshop on Depth Image Analysis
SP  - 126
EP  - 135
VL  - 7854
PB  - Springer Berlin Heidelberg
N2  - 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.
SN  - 0302-9743
SN  - 978-3-642-40302-6
L1  - http://refbase.cvc.uab.es/files/BHP2012.pdf
UR  - http://dx.doi.org/10.1007/978-3-642-40303-3_14
N1  - MILAB; OR;HuPBA;MV
ID  - Miguel Angel Bautista2012
ER  -