Study and Survey on Gesture Recognition Systems
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Abstract (arXiv)
In recent years, there has been a considerable amount of research in the Gesture Recognition domain, mainly owing to the technological advancements in Computer Vision. Various new applications have been conceptualised and developed in this field. This paper discusses the implementation of gesture recognition systems in multiple sectors such as gaming, healthcare, home appliances, industrial robots, and virtual reality. Different methodologies for capturing gestures are compared and contrasted throughout this survey. Various data sources and data acquisition techniques have been discussed. The role of gestures in sign language has been studied and existing approaches have been reviewed. Common challenges faced while building gesture recognition systems have also been explored.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 9 of its 29 references that are in the map. First posted on arXiv 1 Dec 2023.
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9 of 29 references.
References · 9
- 2022Two-Stream Network for Sign Language Recognition and Translationcited by 122
- 2020Transferring Cross-domain Knowledge for Video Sign Language Recognitioncited by 60
- 2021SignBERT: Pre-Training of Hand-Model-Aware Representation for Sign Language Recognitioncited by 59
- 2023Natural Language-Assisted Sign Language Recognitioncited by 46
- 2019Construct Dynamic Graphs for Hand Gesture Recognition via Spatial-Temporal Attentioncited by 22
- 2020CNN+RNN Depth and Skeleton based Dynamic Hand Gesture Recognitioncited by 16
- 2021Unified Learning Approach for Egocentric Hand Gesture Recognition and Fingertip Detectioncited by 6
- 2017Micro Hand Gesture Recognition System Using Ultrasonic Active Sensingcited by 3
- 2023Sign Languague Recognition without frame-sequencing constraints: A proof of concept on the Argentinian Sign Languagecited by 1
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