Review of constraints on vision‐based gesture recognition for human–computer interaction. Issue 1 (18th December 2017)

• Record Type: Journal Article
• Authors: Chakraborty, Biplab Ketan; Sarma, Debajit; Bhuyan, M.K.; MacDorman, Karl F
• Is Part Of: IET computer vision. Volume 12:Issue 1(2018)
• Page Start: 3
• Page End: 15
• Publication Date: 2017-12-18
• Subjects: gesture recognition -- man-machine systems -- feature extraction; vision-based gesture recognition -- human-computer interaction -- hand gesture recognition -- sign language -- medical assistance -- virtual reality -- diverse contexts -- multiple interpretations -- spatio-temporal variations -- complex nonrigid properties -- feature extraction -- feature recognition; Computer vision -- Periodicals; Pattern recognition systems -- Periodicals; 006.37
• DOI: 10.1049/iet-cvi.2017.0052
• Languages: English
• ISSNs: 1751-9632

Abstract

Abstract : The ability of computers to recognise hand gestures visually is essential for progress in human–computer interaction. Gesture recognition has applications ranging from sign language to medical assistance to virtual reality. However, gesture recognition is extremely challenging not only because of its diverse contexts, multiple interpretations, and spatio‐temporal variations but also because of the complex non‐rigid properties of the hand. This study surveys major constraints on vision‐based gesture recognition occurring in detection and pre‐processing, representation and feature extraction, and recognition. Current challenges are explored in detail.