Hybrid Hand Gesture Recognition Based on Depth Camera

• Main Authors: Hu, Jhen-Da, 胡振達
• Other Authors: Tsai, Wen-Jiin
• Format: Others
• Language: en_US
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/7febjn

碩士 === 國立交通大學 === 多媒體工程研究所 === 103 === Hand gesture recognition (HRG) becomes one of most popular topics in recent years because that hand gesture is one of the most natural and intuitive way of communication between Human and machines. It is widely used in HCI (Human-Computer-interaction). In this paper, we proposed a method for hand gesture recognition based on depth camera. Firstly, the hand information within depth image is separated from background based on a specific range of depth. And the contour of hand is detected after segmentation. After that, we estimate centroid of hand, and palm size is calculated by using linear regression. Then, fingers’ states of gesture are estimated depending on information of hand contour. And fingertips are estimated by means of smooth hand contours which reduce number of contours by Douglas-Peucker Algorithm. Finally, we propose a gesture type estimation algorithm to determine which gesture is. The extensive experiments demonstrate that the accuracy rate of our method is from 84.35% to 99.55%, and the mean accuracy is 94.29%.