关键词: 手语识别, 计算机视觉, 深度学习, 神经网络

Abstract:

Sign language, as the main communication channel for deaf and hearing people, plays a crucial role in daily life. With the rapid development of the field of computer vision and deep learning, the field of sign language recognition has also ushered in new opportunities. The advanced methods and technologies used in the research of sign language recognition based on computer vision in recent years are reviewed. Starting from the three branches of static sign language, isolated words and continuous sentence sign language recognition, the common methods and technical difficulties of sign language recognition are systematically explained. The steps of sign language recognition such as image preprocessing, detection and segmentation, tracking, feature extraction, and classification are introduced in detail. It summarizes and analyzes the commonly used algorithms and neural network models for sign language recognition, summarizes and organizes commonly used sign language datasets, analyzes the status quo of different sign language recognition, and finally discusses the challenges and limitations of sign language recognition.

Key words: sign language recognition, computer vision, deep learning, neural network