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.