Research On 3D Gesture Recognition Based On Kinect

Benefit from the development of human-machine interaction theory and technology, human-machine interaction technology based on computer vision is widely used. Recently, application researches based on somatosensory camera became hot topics.In this paper, we introduce a 3D gesture recognition algorithm based on Kinect,which is made by Microsoft company. Our method segment a rough hand area from depth matrix captured by Kinect firstly. Furthermore, we use skin color detection model to get hand contour, and segment a more accurate region for user’s hand. Distance transformation and fingers thinning algorithm will follow on to get centre coordinate of palm and short list of fingertips coordinates respectively. Then, get the total number of fingertips and their 2D fingertips coordinates according to compare the distance between each fingertip and the centre coordinate of palm with our preset threshold. On this basis, we map these 2D fingertips coordinates into depth matrix and use median filtering algorithm to get depth value for each fingertip, which is also called as Z coordinate value. To improve the precision and stability of our gesture recognition algorithm, Kalman Filter is also adopted in this paper. It is used to dynamically track and predict for all of the 3D fingertips coordinates, and match the short list of fingertips coordinates with their prediction coordinates. A vector which contains a consecutive sequence of frames is used to speed up the matching process.In the last part of this paper, we define some gesture events. Then we create two scenes, calculator application scene and block drag scene to validate the feasibility and smoothly of this method we use in this paper. With good performance in gesture recognition accuracy and the smoothly of human-machine interaction, the experimental results show that our method can achieve the expected aim of real-timing and stability.