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Hand gesture recognition using machine learning and infrared information: a systematic literature review
- Source :
- International Journal of Machine Learning and Cybernetics. 12:2859-2886
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- Currently, gesture recognition is like a problem of feature extraction and pattern recognition, in which a movement is labeling as belonging to a given class. A gesture recognition system’s response could solve different problems in various fields, such as medicine, robotics, sign language, human–computer interfaces, virtual reality, augmented reality, and security. In this context, this work proposes a systematic literature review of hand gesture recognition based on infrared information and machine learning algorithms. This systematic literature review is an extended version of the work presented at the 2019 ICSE conference. To develop this systematic literature review, we used the Kitchenham methodology. This systematic literature review retrieves information about the models’ architectures, the implemented techniques in each module, the type of learning used (supervised, unsupervised, semi-supervised, and reinforcement learning), and recognition accuracy classification, and the processing time. Also, it will identify literature gaps for future research.
- Subjects :
- Class (computer programming)
business.industry
Computer science
Feature extraction
Context (language use)
Machine learning
computer.software_genre
ComputingMethodologies_PATTERNRECOGNITION
Systematic review
Artificial Intelligence
Gesture recognition
Pattern recognition (psychology)
Reinforcement learning
Augmented reality
Computer Vision and Pattern Recognition
Artificial intelligence
business
computer
Software
Subjects
Details
- ISSN :
- 1868808X and 18688071
- Volume :
- 12
- Database :
- OpenAIRE
- Journal :
- International Journal of Machine Learning and Cybernetics
- Accession number :
- edsair.doi...........016b383cefc79dac78f0cdeaea892595