Multimodal Features

Information extracted from multiple sensory channels or data types—such as combining visual (RGB), depth, audio, and skeletal data—to improve recognition accuracy. In accessibility systems, multimodal approaches often outperform single-modality methods because different data sources provide complementary information. For sign language recognition, combining hand shape appearance with body skeleton positions captures both fine-grained hand gestures and broader arm movements.