Hand Detection and Tracking Using Depth and Color Information

The detection and tracking of a hand is an emerging research issue now-a-days to control the devices by hand motion. Conventional hand detection methods use color and shape information from a RGB camera. With the recent advent of the depth camera, some researchers show that they can improve the performance of hand detection by combining the color (or intensity) information with the information from the depth camera. In this paper, we propose a novel method for hand detection using both color and depth information from Microsoft’s Kinect device. The proposed method extract the candidate hand regions from the depth image and select the best candidate based on the color and shape feature of each candidate regions. Then the contour of the selected candidate is determined in the higher resolution RGB image to improve the positional accuracy. For the tracking of the detected hand, we propose the boundary tracking method based on Generalized Hough Transform (GHT). The experimental results show that proposed method can improve the accuracy of hand motion detection over conventional methods.