3-D gesture recognition from serial range image

In this research, the recognition of gesture in 3-D space is examined by using serial range images obtained by a real-time 3-D measurement system developed in our laboratory. Using this system, it is possible to obtain time sequences of range, intensity and color data for a moving object in real-time without assigning markers to the targets. At first, gestures are tracked in 2-D space by calculating 2-D flow vectors at each points using an ordinal optical flow estimation method, based on time sequences of the intensity data. Then, location of each point after 2-D movement is detected on the x-y plane using thus obtained 2-D flow vectors. Depth information of each point after movement is then obtained from the range data and 3-D flow vectors are assigned to each point. Time sequences of thus obtained 3-D flow vectors allow us to track the 3-D movement of the target. So, based on time sequences of 3-D flow vectors of the targets, it is possible to classify the movement of the targets using continuous DP matching technique. This tracking of 3-D movement using time sequences of 3-D flow vectors may be applicable for a robust gesture recognition system.