Indian Journal of Science and Technology
Year: 2023, Volume: 16, Issue: 16, Pages: 1221-1229
M Sowmya1*, M Balasubramanian2, K Vaidehi3
1Research Scholar, Department of CSE, Annamalai University, Annamalai Nagar, India
2Associate Professor, Department of CSE, Annamalai University, Annamalai Nagar, India
3Associate Professor, Department of CSE, Stanley College of Engineering and Technology for Women, Hyderabad, India
Email: [email protected]
Received Date:27 January 2023, Accepted Date:30 March 2023, Published Date:24 April 2023
Objective: To develop a real-time application for human behavior classification using 2- Dimensional Convolution Neural Network, VGG16 and ResNet50. Methods: This study provides a novel system which considers sitting, standing and walking as normal human behaviors. It consists of three major steps: dataset collection, training, and testing. In this work real time images are used. In human behavior classification dataset there are 2271 trained images and 539 testing images. Findings: The Convolution Neural Network (CNN), VGG16 and ResNet50 are trained using human normal behavior images. Novelty: The dataset namely human behavior classification dataset is used in this work and the experimental results has shown that on human behavior classification ResNet50 has outperformed with accuracy of 99.72% compared to VGG16 and 2D-CNN. This work can detect the three normal behaviors of humans in an unconstrained laboratory environment.
Keywords: Deep Learning; 2D Convolution Neural Network (CNN); Human Behavior Classification; ADAM Optimizer; VGG16; ResNet50
© 2023 Sowmya et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)
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