Gesture Recognition: A Survey

TLDR

Gesture recognition involves identifying meaningful human motion expressions—hands, arms, face, head, or body—and is crucial for designing intelligent, efficient human‑computer interfaces, with applications spanning sign language, medical rehabilitation, and virtual reality. In this paper, we provide a survey on gesture recognition with particular emphasis on hand gestures and facial expressions. The survey discusses applications of hidden Markov models, particle filtering, finite‑state machines, optical flow, skin color, and connectionist models, and highlights existing challenges and future research possibilities.

Abstract

Gesture recognition pertains to recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head, and/or body. It is of utmost importance in designing an intelligent and efficient human-computer interface. The applications of gesture recognition are manifold, ranging from sign language through medical rehabilitation to virtual reality. In this paper, we provide a survey on gesture recognition with particular emphasis on hand gestures and facial expressions. Applications involving hidden Markov models, particle filtering and condensation, finite-state machines, optical flow, skin color, and connectionist models are discussed in detail. Existing challenges and future research possibilities are also highlighted