由於人機交互系統的發展,用於一般相機鏡頭的手部追蹤技術受到很多的關注。對於這項工作來說,我們改良了近期有名的物件追蹤演算法,稱Tracking-Learning-Detection (TLD),以利於進行高效率的手部追蹤應用。具體來說,我們結合了反向投影方法來適應其中的追蹤及偵測機制以達成手部追蹤的各種情況。同時,我們也提出利用手部追蹤軌跡來提高TLD分類的準確度。在實驗結果表明了此改良的TLD成功地實現人機交互應用的目標。 Hand tracking on general camera has received a lot of attention due to numerous applications of human computer interaction. In this work, we improve a recently famous object tracking algorithm, named Tracking-Learning-Detection (TLD), in order to do efficient and effective hand tracking. Specifically, we incorporate the back projection method to adapt the tracking and detection mechanism for hand tracking. We also propose to use hand trajectories to advance the accuracy of the TLD classifier. Experimental results show that the revised TLD successfully accomplishes the target human computer interaction.