Real-Time Robust Hand Tracking Based on Camshift and Motion Velocity

Although a lot of works have been done in the domain of hand tracking, it is still a challenge to robustly tracking hand motion. Traditional Camshift algorithm which can efficiently tracking object in a simple scene is sensitive to the changing of background, other variant such as Camshift&Kalman tracking is still not robust enough to give a reliable result. This paper proposes a real-time hand tracking algorithm just using normal camera. KLT feature tracking is used to tracking good features in the hand, and we use this tracking result to calculate the main velocity of hand motion. Additionally, global velocity which is calculated from probability of Bayesian skin color is used to refine the velocity of hand motion. After this step, we can update Camshift tracking window using the velocity of hand. Finally Camshift is used to detect a more precise hand region. This approach is relatively insensitive to background, achieving robust tracking performance in real-time.

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