DocumentCode :
1836850
Title :
Hand tracking and pose recognition via depth and color information
Author :
Cheng Tang ; Yongsheng Ou ; Guolai Jiang ; Qunqun Xie ; Yangsheng Xu
Author_Institution :
Shenzhen Inst. of Adv. Technol., Shenzhen, China
fYear :
2012
fDate :
11-14 Dec. 2012
Firstpage :
1104
Lastpage :
1109
Abstract :
As one of the most natural and intuitive way of communication between people and machines, hand gesture is widely used in HCI (Human-Computer-interaction). In this paper, we proposed a novel method for hand tracking and pose recognition based on Kinect. For hand tracking, skin information is used for initialization of hand segmentation, and then a region growing algorithm is applied in the depth image to separate hand from other skin colored objects. Finally, a Kalman filter is used for tracking hand in 3D space. For hand recognition, we decompose the problem of recognizing hand pose into recognizing different finger states. Both contour information of the whole hand and depth information inside the contour are considered for finger states recognition. It is shown in the experiments that our system can track the hand robustly and recognize more than 90% of the hand poses we define for our depth image database.
Keywords :
Kalman filters; gesture recognition; human computer interaction; image segmentation; object tracking; palmprint recognition; pose estimation; visual databases; 3D space; HCI; Kalman filter; Kinect; contour information; depth image database; finger state recognition; gesture recognition; hand gesture; hand segmentation; hand tracking; human computer interaction; pose recognition; region growing algorithm; skin colored objects;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2012 IEEE International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4673-2125-9
Type :
conf
DOI :
10.1109/ROBIO.2012.6491117
Filename :
6491117
Link To Document :
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