In this paper we describe a real-time system for detecting pointing gestures and estimating the direction of pointing using stereo cameras. Previously, similar systems were implemented using color-based blob trackers, which relied on effective skin color detection; this approach is sensitive to lighting changes and the clothing worn by the user. In contrast, we used a stereo system that produces dense disparity maps in real-time. Disparity maps are considerably less sensitive to lighting changes. Our system subtracts the background, analyzes the foreground pixels to break the body into parts using a robust mixture model, and estimates the direction of pointing. We have tested the system on both coarse and fine pointing by selecting the targets in a room and controlling the cursor on a wall screen, respectively.
Index Terms:
Visual tracking, vision based user interfaces, human body tracking, gesture analysis, stereo images, disparity images, disparity maps, range images, statistical models
Citation:
Nebojsa Jojic, Thomas Huang, Barry Brumitt, Brian Meyers, Steve Harris, "Detection and Estimation of Pointing Gestures in Dense Disparity Maps," fg, pp.468, Fourth IEEE International Conference on Automatic Face and Gesture Recognition (FG'00), 2000