一种改进的TLD动态手势跟踪算法

A Dynamic Gesture Tracking Algorithm Based on the Improved Tracking-Learning-Detection

针对目前动态手势跟踪算法TLD(跟踪-学习-检测)算法在手势目标遮挡后易出现跟踪漂移的不足,提出了一种改进的TLD动态手势跟踪算法.在跟踪器跟踪成功后,引入遮挡窗的方法进行手势目标遮挡的判定.若出现部分遮挡,则由TLD学习器处理;若出现严重遮挡,则在TLD的跟踪器中加入卡尔曼滤波器来预测估计当前帧中手势可能存在的区域,缩小跟踪器的搜索范围,提高跟踪器的处理速度;并在TLD检测器中加入基于马尔可夫模型的方向预测器,缩小检测器的检测范围,增强检测器对相似手势轨迹的判别能力.实验结果证明,改进后的TLD算法在不同的实验环境下均有较强的鲁棒性,能够快速准确地进行动态手势运动轨迹的跟踪,并且改善了手势目标遮挡后易出现跟踪漂移的问题.

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.