Tracking and recognition algorithms for dynamic hand gestures have been studied and interactive volumetric three-dimensional (3D) display based on dynamic hand gesture control has been implemented. Volumetric 3D display can present images with physical depth cues in the true 3D space, where images can be viewed from almost any angle without any special eyewear. With vision-based hand gesture control, viewers can interact with volumetric 3D display from any viewpoint. Firstly, tracking region containing a special static hand posture is initialized from frame-differencing images. Meanwhile, a skin color model is built based on the region. Then positions of KLT features in the initial region are updated using optical flow tracking method and adjusted with the “flock of features” algorithm and the learned skin color model. Thereafter, through coordinate transformation and encoding according to eight-directional Freeman chain code, gesture observation sequence is generated for recognition. Finally, a pre-specified gesture symbol is decided by Hidden Markov Model (HMM) evaluation using a trained gesture HMM set. Experiments are conducted for the interactive volumetric display based on dynamic hand gesture control. Experimental results show that with these gesture tracking and recognition algorithms, the average recognition rate is high up to 93%, the average response time is less than 40 ms, and interactions can be well performed from arbitrary viewpoint.