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A Structured and Methodological Review on Vision-Based Hand Gesture Recognition System
Fahmid Al Farid1, Noramiza Hashim1, Junaidi Abdullah1
1Faculty of Computing and Informatics, Multimedia University, Persiaran Multimedia, Cyberjaya 63100, Malaysia.
Journal of Imaging
|June 23, 2022
Summary
This review analyzes vision-based hand gesture recognition challenges and advancements from 2012-2022. It identifies limitations in image acquisition, segmentation, feature extraction, and classification, highlighting areas for future research in real-time gesture recognition systems.
Area of Science:
- Computer Vision
- Human-Computer Interaction
- Artificial Intelligence
Background:
- Vision-based hand gesture recognition is crucial for intuitive human-computer interaction.
- Real-time implementation faces challenges in image acquisition, segmentation, tracking, feature extraction, and classification.
- Existing research exhibits significant variability in recognition accuracy, ranging from 68% to 97%.
Purpose of the Study:
- To systematically review and analyze vision-based hand gesture recognition research from 2012 to 2022.
- To identify limitations and areas for improvement across the entire gesture recognition pipeline.
- To provide a categorized resource of notable research and methodologies in the field.
Main Methods:
- Conducted a literature review using specific keywords across major online databases, identifying 108 relevant articles.
- Categorized and summarized methodologies from selected research works.
- Analyzed recognition accuracy and identified common limitations.
Main Results:
- Identified key challenges in image acquisition, segmentation, feature extraction, and classification stages.
- Documented a wide range of recognition accuracies, averaging 86.6%.
- Highlighted limitations including ambiguous gesture interpretations and complex hand articulations.
Conclusions:
- Significant progress has been made, but real-time vision-based hand gesture recognition remains challenging.
- Further research is needed to address limitations in handling diverse interpretations and non-rigid hand dynamics.
- This review offers a comprehensive overview and categorization of current techniques, guiding future development.
