Feature extraction from 2D gesture trajectory in dynamic hand gesture recognition

Vision-based hand gesture recognition is a popular research topic for human-machine interaction (HMI). We have earlier developed a model-based method for tracking hand motion in complex scene by using Hausdorff tracker. In this paper, we now propose to extract certain features from the gesture trajectory so as to identify the form of the trajectory. Thus, these features can be efficiently used for trajectory guided recognition/classification of hand gestures. Our experimental results show 95% of accuracy in identifying the forms of the gesture trajectories. This indicates that the trajectory features proposed in this paper are appropriate for defining a particular gesture trajectory.