Dynamic Gesture Recognition and Interaction of Monocular Camera Based on Deep Learning - SUNBo wen; YU Feng (Journal of Harbin University of Science and Technology)
Most of the existing gesture recognition applications are based on specific devices, such as Kinect, Leap Motion, etc. Because of its price and practicability, it can not be widely used. Monocular camera is the most common accessory of computer or mobile devices. With the corresponding gesture recognition and interaction algorithm, gesture interaction can be carried out. In this paper, the algorithm of gesture recognition and interaction based on monocular camera is studied. The monocular camera captures the image, uses the skin color to segment the image, and removes the noise points according to the contour area to get the binary image of the gesture image. Then, the matrix of binary graph is introduced into the neural network as a parameter for deep learning pattern recognition. Through convolution and fullconnected network structure, as well as optimization of parameter selection and prevention of overfitting, combined with fingertip detection and elimination algorithm, the recognition accuracy is improved. In the aspect of gesture interaction, the motion on the plane of gesture image is judged by the change of gesture center of gravity, and the displacement is detected to prevent the sudden change of gesture image position caused by the interference. In the front and back movement of gestures, the area of different gestures is compensated for and adjusted by the size of gesture images, so as to reduce the interference caused by the area changes caused by different gestures.