2D Image Based Digital Anthropometry Using Deep Learning Approach

Authors

  • Ravindra B. Gadhiya, Nilesh B. Kalani

Keywords:

Digital Anthropometry, Semantic Segmentation, DeepLabV3 , Pose Estimation, BlazePose

Abstract

Anthropometry is a tool which is widely used for human body parts measurement across diverse field of science. There are several conventional tools available for measurement like measure tape, clippers etc. These conventional anthropometric devices are quick being changed via way of means of modern AI based systems. Digital anthropometry (DA) is a relatively new technique for measuring the dimensions of human body parts. Estimating the pose of a human with the assist of a photograph or a video has these days acquired extensive interest from the medical community. An aim of the research work is to introduce Deep learning concept in digital anthropometry and to develop a novel 2D image based digital measurement system which is more efficient to deal with various limitations of existing techniques. Here for body parts measurement, advanced models of the segmentation and pose estimation is employed to get better results. Also, existing models for anthropometry is implemented. The analysis and comparison of the results with the other methods is presented for better understanding.

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Published

09.07.2024

How to Cite

Ravindra B. Gadhiya. (2024). 2D Image Based Digital Anthropometry Using Deep Learning Approach. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 884 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6571

Issue

Vol. 12 No. 22s (2024)

Section

Research Article

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