TY - GEN
T1 - Attentive gesture recognition
AU - Dodge, Samuel F.
AU - Karam, Lina
PY - 2012
Y1 - 2012
N2 - This paper presents a novel method for static gesture recognition based on visual attention. Our proposed method makes use of a visual attention model to automatically select points that correspond to fixation points of the human eye. Gesture recognition is then performed using the determined visual attention fixation points. For this purpose, shape context descriptors are used to compare the sparse fixation points of gestures for classification. Simulation results are presented in order to illustrate the performance of the proposed perceptual-based attentive gesture recognition method. The proposed method not only helps in the development of more natural user-centric interactive interfaces but is also able to achieve a 96.42% classification accuracy on the Triesch database of hand postures, which is superior to other methods presented in the literature.
AB - This paper presents a novel method for static gesture recognition based on visual attention. Our proposed method makes use of a visual attention model to automatically select points that correspond to fixation points of the human eye. Gesture recognition is then performed using the determined visual attention fixation points. For this purpose, shape context descriptors are used to compare the sparse fixation points of gestures for classification. Simulation results are presented in order to illustrate the performance of the proposed perceptual-based attentive gesture recognition method. The proposed method not only helps in the development of more natural user-centric interactive interfaces but is also able to achieve a 96.42% classification accuracy on the Triesch database of hand postures, which is superior to other methods presented in the literature.
KW - Static gesture recognition
KW - human computer interaction
KW - visual attention
UR - http://www.scopus.com/inward/record.url?scp=84875869762&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84875869762&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2012.6466824
DO - 10.1109/ICIP.2012.6466824
M3 - Conference contribution
AN - SCOPUS:84875869762
SN - 9781467325332
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 177
EP - 180
BT - 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
T2 - 2012 19th IEEE International Conference on Image Processing, ICIP 2012
Y2 - 30 September 2012 through 3 October 2012
ER -