A Dynamic Gesture Tracking Algorithm Based onthe Improved Tracking-Learning-Detection

An improved dynamic gesture tracking algorithm based on TLD(tracking-learning-detection) is proposed to solve the problem of tracking drift in dynamic gesture tracking when the gesture is occluded. After tracking the gesture target successfully, an occlusion window method is incorporated to determine the degree of the gesture occlusion. When the gesture is partially occluded, the TLD learner is utilized to solve the problem. When the gesture is seriously covered, the Kalman filter is added into the TLD tracker to estimate the area in the current frame where the gesture may exist. Then the search range is reduced, which improves the processing speed of the tracker. Meanwhile, the direction predictor based on Markov model is added into the TLD detector to reduce the detection range of the detector and enhance the discrimination ability for the similar gesture trajectory. The experiment shows that the improved TLD algorithm has strong robustness in different environments and can quickly and accurately track the dynamic gesture trajectory. The proposed algorithm also improves the tracking drift problem when the gesture is occluded.