DocumentCode :
3447482
Title :
Static Human Gesture grading based on Kinect
Author :
Linwan Liu ; Xiaoyu Wu ; Linglin Wu ; Tianchu Guo
Author_Institution :
Dept. of Digital Media Technol., Commun. Univ. of China, Beijing, China
fYear :
2012
fDate :
16-18 Oct. 2012
Firstpage :
1390
Lastpage :
1393
Abstract :
We presented a static human gesture grading system based on the skeletal tracking module of Kinect sensor. We captured the 2-D skeleton wireframe of a poser´s body and represented the data as limb vectors. The distance metric is defined as the included angle array computed between the real-time and the standard gesture. We proposed a grading formula to simulate the gesture judging scenario, of which the parameters can be adaptively computed or manually set. The system worked efficiently under the low computational complexity and was robust to input noise.
Keywords :
gesture recognition; image classification; image sensors; pose estimation; target tracking; 2D skeleton wireframe; Kinect sensor; angle array; distance metric; gesture classification; gesture judging scenario; human pose recognition; limb vectors; low computational complexity; poser body; realtime gesture; skeletal tracking module; standard gesture; static human gesture grading system; Arrays; Humans; Legged locomotion; Real-time systems; Skeleton; Standards; Vectors; Kinect; gesture grading; limb vectors; skeleton data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2012 5th International Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-0965-3
Type :
conf
DOI :
10.1109/CISP.2012.6469917
Filename :
6469917
Link To Document :
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