Video-Based Chinese Sign Language Recognition Using Convolutional Neural Network

Convolutional neural network (CNN) has been widely used in computer vision tasks recently and achieved remarkable success. This paper presents a novel video-based recognition approach using CNN for Chinese Sign Language (CSL). The proposed method extracts upper body images directly from videos, and employs a pre-training convolutional network model to recognize the gesture in the image. The new method simplifies the hand-shape segmentation, and avoid information loss in feature extraction. We evaluate the method on our self-built dataset includes 40 daily vocabularies, and show that the proposed approach has good performance on sign language recognition task, with accuracy reaching to 99%.