Abstract
To communicate with one another hand, gesture is very important. The task of using the hand gesture in technology is influenced by a very common way humans communicate with the natural environment. The recognizing and finding pose estimation of hand comes under the area of hand gesture analysis. To find out the gesturing hand is very difficult than finding the another part of the human body because the hand is smaller in size. The hand has greater complexity and more challenges due to differences between the cultural or individual factors of users and gestures invented from ad hoc. The complication and divergences of finding hand gestures will deeply affect the recognition rate and accuracy. This paper emphasizes on summary of hand gestures technique, recognition methods, merits and demerits, various applications, available data sets, and achieved accuracy rate, classifiers, algorithm, and gesture types. This paper also scrutinizes the performance of traditional and deep learning methods on dynamic hand gesture recognition.
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The authors would like to acknowledge the Cyber Forensic and Malware Analysis Lab, Department of Information Technology, Delhi Technological University, New Delhi, India, for providing me necessary resources to carry out the research.
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Tripathi, R., Verma, B. Survey on vision-based dynamic hand gesture recognition. Vis Comput 40, 6171–6199 (2024). https://doi.org/10.1007/s00371-023-03160-x
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DOI: https://doi.org/10.1007/s00371-023-03160-x