Sign Language Recognition

A computer vision and machine learning task focused on automatically detecting and classifying signs from video input. Sign language recognition ranges from isolated sign recognition (identifying individual signs) to continuous sign recognition (interpreting sequences of signs in natural signing). Effective recognition systems must account for multiple simultaneous parameters — handshape, hand location, movement, palm orientation, facial expression, and body posture — as well as individual variation in signing style, speed, and regional dialects. While significant progress has been made on isolated sign recognition using benchmark datasets, continuous recognition in real-world conditions remains a major challenge. The Deaf community has expressed concern that recognition technology often prioritizes technical metrics over practical utility, and that development frequently proceeds without meaningful Deaf involvement.