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DOI: 10.14569/IJACSA.2024.0151167
PDF

Yolov5-Based Attention Mechanism for Gesture Recognition in Complex Environment

Author 1: Deepak Kumar Khare
Author 2: Amit Bhagat
Author 3: R. Vishnu Priya

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 11, 2024.

  • Abstract and Keywords
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Abstract: Object detection is a fundamental task in gesture recognition, involving identifying and localising human hand or body gestures within images or videos amidst varying environmental conditions. To address the inadequate recognition rate of gesture detection algorithms in intricate surroundings caused by issues such as inconsistent illumination, background colors resembling skin tones, and diminutive gesture scales, a gesture recognition approach termed HD-YOLOv5s is presented. An adaptive Gamma image enhancement preprocessing technique grounded in Retinex theory is employed to mitigate the effects of lighting variations on gesture recognition efficacy. A feature extraction network incorporating an adaptive convolutional attention mechanism (SKNet) is developed to augment the network's feature extraction efficacy and mitigate background interference in intricate situations. A novel bidirectional feature pyramid architecture is implemented in the feature fusion network to fully leverage low-level features, thereby minimizing the loss of shallow semantic information and enhancing the detection accuracy of small-scale gestures. A cross-level connection strategy is employed to enhance the model's detection efficiency. To assess the efficacy of the suggested technique, experiments were performed on a custom dataset featuring diverse lighting intensity fluctuations and the publicly available NUS-II dataset with intricate backdrops. The recognition rates attained were 99.5% and 98.9%, respectively, with a detection time per frame of about 0.01 to 0.02 seconds.

Keywords: Gesture recognition; Yolov5; object detection; attention mechanism; bidirectional feature pyramid

Deepak Kumar Khare, Amit Bhagat and R. Vishnu Priya, “Yolov5-Based Attention Mechanism for Gesture Recognition in Complex Environment” International Journal of Advanced Computer Science and Applications(IJACSA), 15(11), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0151167

@article{Khare2024,
title = {Yolov5-Based Attention Mechanism for Gesture Recognition in Complex Environment},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151167},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151167},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {11},
author = {Deepak Kumar Khare and Amit Bhagat and R. Vishnu Priya}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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