基于深度图像的人体运动姿态跟踪和识别算法

由于人体运动的复杂性，现有基于低质量深度图像的三维立体姿态跟踪和识别 方法的准确性较低、鲁棒性较差。针对低质量深度图像的人体运动姿态和识别问题，本文设 计了一种基于三步搜索算法的人体运动姿态的跟踪和识别方法。该方法首先对获取的深度信 息进行分析，从而判定人体轮廓；然后通过基于深度图像的骨骼跟踪方法跟踪特定骨骼点， 并采用三步搜索算法进行运动估计，跟踪获取人体运动轨迹；最后利用获取的骨骼点坐标实 现人体运动姿态的识别。实验结果表明，该算法克服光照影响的鲁棒性较强，且能有效地提 高人体运动姿态跟踪与识别的准确性。

Depth Image Based Human Motion Tracking and Recognition Algorithm

In the three dimensional vision system, recognizing and tracking human motion g esture is the crucial step to identify human motion in machine vision field. Due to the complexity of human motion, the existing methods, based on the low quality depth images, canno t provide a high accuracy and a good robust for 3D gesture tracking and recogn ition. Adressing the low quality depth images of the human gesture tracking and recognition, a method is presented based on three step search algorithm. Firstl y, the obtained depth images are analyzed to achieve the human body contour. The n, the settled special skeleton points are tracked based on the depth images, an d the three-step search algorithm is utilized to access the motion estimation a nd get the track motion of the human gesture. Finally, the motion recognition is achieved by using the obtained skeleton point coordinates. Experimental results show that the proposed method is robust to overcome the impact of the illuminat ion, and it also provides improved accurate results of human motion tracking and gesture recognition.