Hand Detection Based on YOLOv3

Hand detection is paid more attention to in the field of augmented reality, which can enhance user experience of human–computer interaction. It is more and more popular to use deep neural networks to research hand detection. A new method of hand detection based on YOLOv3 Model is proposed in our work. Our target is to contribute to a real-time hand detection system to make it more accuracy and convenient for the experience of the user and can apply in all aspects of our life. 11 K hands dataset is used to perfrom the experiments and the result is sound.