Hand Gesture Recognition Based on Computer Vision: A Review of Techniques.
computer vision
hand gesture
hand posture
human–computer interaction (HCI)
Journal
Journal of imaging
ISSN: 2313-433X
Titre abrégé: J Imaging
Pays: Switzerland
ID NLM: 101698819
Informations de publication
Date de publication:
23 Jul 2020
23 Jul 2020
Historique:
received:
23
05
2020
revised:
15
07
2020
accepted:
21
07
2020
entrez:
30
8
2021
pubmed:
31
8
2021
medline:
31
8
2021
Statut:
epublish
Résumé
Hand gestures are a form of nonverbal communication that can be used in several fields such as communication between deaf-mute people, robot control, human-computer interaction (HCI), home automation and medical applications. Research papers based on hand gestures have adopted many different techniques, including those based on instrumented sensor technology and computer vision. In other words, the hand sign can be classified under many headings, such as posture and gesture, as well as dynamic and static, or a hybrid of the two. This paper focuses on a review of the literature on hand gesture techniques and introduces their merits and limitations under different circumstances. In addition, it tabulates the performance of these methods, focusing on computer vision techniques that deal with the similarity and difference points, technique of hand segmentation used, classification algorithms and drawbacks, number and types of gestures, dataset used, detection range (distance) and type of camera used. This paper is a thorough general overview of hand gesture methods with a brief discussion of some possible applications.
Identifiants
pubmed: 34460688
pii: jimaging6080073
doi: 10.3390/jimaging6080073
pmc: PMC8321080
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng