DocumentCode :
3565866
Title :
Dynamic contour matching for hand gesture recognition from monocular image
Author :
Chonbodeechalermroong, Ariyawat ; Chalidabhongse, Thanarat H.
Author_Institution :
Dept. of Comput. Eng., Chulalongkorn Univ., Bangkok, Thailand
fYear :
2015
Firstpage :
47
Lastpage :
51
Abstract :
Hand gestures are used widely in communication. An important example is using in the sign languages. Many hand gesture silhouettes are the part of other hand gesture silhouettes. For example, V sign gesture is a part of the high five gesture, because we can create high five gesture silhouettes from the V sign gesture silhouettes by extending the other three fingers. Here we propose the partial contour matching algorithm for gesture classification. Our classification is to find the deepest gesture in a tree such that none of more its children are the part of a sample silhouette.
Keywords :
image classification; image matching; sign language recognition; dynamic contour matching; gesture classification; hand gesture recognition; monocular image; partial contour matching algorithm; Accuracy; Classification algorithms; Gesture recognition; Image color analysis; Image segmentation; Skin; Thumb; Sign language; hand Gesture recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering (JCSSE), 2015 12th International Joint Conference on
Type :
conf
DOI :
10.1109/JCSSE.2015.7219768
Filename :
7219768
Link To Document :
بازگشت