Name
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ROBIO.2012.6491117 | ROBIO |
Keywords | Field | DocType |
kalman filter,palmprint recognition,kalman filters,human computer interaction,finger state recognition,depth image database,visual databases,image segmentation,pose estimation,region growing algorithm,pose recognition,3d space,hand segmentation,object tracking,contour information,hand tracking,skin colored objects,hci,gesture recognition,kinect,hand gesture | Computer vision,Colored,Region growing algorithm,Computer science,Segmentation,Gesture,Gesture recognition,Kalman filter,Artificial intelligence,Initialization,Image database | Conference |
ISBN | Citations | PageRank |
978-1-4673-2125-9 | 3 | 0.47 |
References | Authors | |
10 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cheng Tang | 1 | 5 | 1.91 |
| Yongsheng Ou | 2 | 243 | 42.32 |
| Guolai Jiang | 3 | 31 | 3.55 |
| Qunqun Xie | 4 | 5 | 1.23 |
| Yangsheng Xu | 5 | 1541 | 245.29 |