International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Vision-Based Gesture Interaction Without Peripheral Devices |
|---|---|
| ABSTRACT | The Vision-Based Hand Gesture Interaction System is designed to enable touch-free human-computer interaction by replacing traditional input devices such as mouse and keyboard with hand gestures. The system uses a standard RGB camera to capture real-time hand movements and applies computer vision techniques using OpenCV and MediaPipe to detect and track hand landmarks accurately. Recognized gestures are processed through predefined logic or machine learning models and mapped to system commands such as cursor movement, clicking, scrolling, brightness control, and volume adjustment. The system ensures smooth real-time performance with minimal delay, providing a user-friendly and efficient interaction experience. Designed with accessibility and innovation in mind, this solution supports contactless interaction, enhances usability for physically challenged individuals, and reduces dependency on hardware peripherals, thereby improving the overall human-computer interaction process. |
| AUTHOR | DR. R. JOTHILAKSHMI, E. DHARSHINI, S. DHARSHINI, V. SWATHI Associate Professor, Department of Information Technology, R.M.D. Engineering College, Chennai, Tamil Nadu, India Student, Department of Information Technology, R.M.D. Engineering College, Chennai, Tamil Nadu, India |
| VOLUME | 182 |
| DOI | DOI: 10.15680/IJIRCCE. 2026.1403022 |
| pdf/22_Vision-Based Gesture Interaction Without Peripheral Devices.pdf | |
| KEYWORDS | |
| References | [1] Mukhopadhyay A., Chakrabarty A., Das A. A., and Sarkar A., Hand Gesture Based Recognition System, Proceedings of the 7th International Conference on Electronics, Materials Engineering and Nano-Technology (IEMENTech), 18–20 December 2023, IEEE, 2024. [2] Hashi A. O., Mohd Hashim S. Z., and Asamah A. B., A Systematic Review of Hand Gesture Recognition: An Update from 2018 to 2024, IEEE Access, Vol. 12, 2024, pp. 1–28. [3] Lou X., Vision-Based Hand Gesture Recognition Technology, Proceedings of the 3rd International Conference on Mechatronics and Smart Systems, 2025, pp. 54–59. [4] Jalayer R., Jalayer M., Orsenigo C., and Tomizuka M., A Review on Deep Learning for Vision-Based Hand Detection, Hand Segmentation and Hand Gesture Recognition in Human–Robot Interaction, Robotics and Computer-Integrated Manufacturing, Vol. 97, February 2026. |
