Gesture Recognition a Survey
IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART C: APPLICATIONS AND REVIEWS, VOL. 37, NO. 3, MAY 2007
311
Gesture Recognition: A Survey
Sushmita Mitra, Senior Member, IEEE, and Tinku Acharya, Senior Member, IEEE
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. Index Terms—Face recognition, facial expressions, hand gestures, hidden Markov models (HMMs), soft computing, optical flow.
I. INTRODUCTION
I
N THE PRESENT day framework of interactive, intelligent computing, an efficient human–computer interaction is assuming utmost importance in our daily lives. Gesture recognition can be termed as an approach in this direction. It is the process by which the gestures made by the user are recognized by the receiver. Gestures are expressive, meaningful body motions involving physical movements of the fingers, hands, arms, head, face, or body with the intent of: 1) conveying meaningful information or 2) interacting with the environment. They constitute one interesting small subspace of possible human motion. A gesture may also be perceived by the environment as a compression technique for the information to be transmitted elsewhere and subsequently reconstructed by the receiver. Gesture recognition has wide-ranging applications [1] such as the following: r
311
Gesture Recognition: A Survey
Sushmita Mitra, Senior Member, IEEE, and Tinku Acharya, Senior Member, IEEE
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. Index Terms—Face recognition, facial expressions, hand gestures, hidden Markov models (HMMs), soft computing, optical flow.
I. INTRODUCTION
I
N THE PRESENT day framework of interactive, intelligent computing, an efficient human–computer interaction is assuming utmost importance in our daily lives. Gesture recognition can be termed as an approach in this direction. It is the process by which the gestures made by the user are recognized by the receiver. Gestures are expressive, meaningful body motions involving physical movements of the fingers, hands, arms, head, face, or body with the intent of: 1) conveying meaningful information or 2) interacting with the environment. They constitute one interesting small subspace of possible human motion. A gesture may also be perceived by the environment as a compression technique for the information to be transmitted elsewhere and subsequently reconstructed by the receiver. Gesture recognition has wide-ranging applications [1] such as the following: r