目前運用深度感測器建立人體骨架是常用的人機互動解決方法， 快速且精準，但當人在某些動作下，例如坐姿、躺姿、腿部交叉，前兩種由於與背景物體太過接近，深度感測器無法分辨出人以及物體，而最後一種會因為雙腳重疊導致分辨不出其前後關係，都將會使骨架錯亂，追蹤結果失敗。 本論文目前針對腿部交叉所發生的錯誤進行補正。而為解決這問題，本研究提出以深度影像的骨架追蹤結果為主，當發生腿部交叉時，則運用彩色影像作為輔助，重新建立骨架，使追蹤結果保持正確。 The common solution of human-computer interaction is used depth sensor to establish human skeleton, but the skeleton information will be incorrect in some action such as sitting posture, lying posture, and legs crossed. The first two posture that human body is too close with background object, the sensor cannot recognize human and background. The last one, leg crossed, because cannot recognize the relationship of crossing leg. When people in one of these three posture, the skeleton tracking will be failed. In this thesis, we focus on fixing the bug on legs crossed posture. To solve this problem, we proposes a depth image of the skeleton tracking, when a cross-leg, then the color images be used as an aid to re-establish the skeleton, so as to maintain the correct tracking results.
