UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 12 | Issue 10 | October 2025

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Published in:

Volume 12 Issue 3
March-2025
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2503719


Registration ID:
557873

Page Number

h152-h158

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Title

Automatic Human Body Measurement using Computer Vision & Media Pipe

Abstract

Accurate measurements of the human body are important in a variety of settings, including tailoring, fitness tracking, and healthcare. Conventional measurement approaches usually involve human intervention which can be slow, error-likely, and inconvenient. This project describes an approach to automate human body measurements using basic computer vision methods and the Media pipe framework. The system measures body dimensions using images as inputs, and uses Mediapipe's pose estimation and tracking as a way to identify key landmarks on the human body. The landmarks are then used in conjunction with computer vision algorithms to accurately calculate the measurements of interest (height, waist circumference, arm length, etc.). The system is also designed to measure accurately using calibration techniques to account for scaling and posture of the person being measured. The system is easy to use, requiring minimal input from the user, and works with readily available mobile phones or other devices. This technology attempts to simplify the current options available in the tailoring and fashion environments by providing a cost-efficient, productive, and easy option to assess body measurements when compared with conventional structure.The project also investigates the possibilities for integration with augmented reality (AR) for real-time visualization of measurements and designs to improve usability. The system was tested on a variety of datasets to verify that it would perform robustly across different body types, lighting conditions, and environments. The results demonstrate the potential of combining Mediapipe's real-time capabilities with some custom computer vision algorithms to create a scalable and practical solution to automated human body measurement.

Key Words

3D Mesh Generation, Media Pipe, Landmark Detection, Open3D, MPII Human Pose, COCO Dataset

Cite This Article

"Automatic Human Body Measurement using Computer Vision & Media Pipe", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.h152-h158, March-2025, Available :http://www.jetir.org/papers/JETIR2503719.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Automatic Human Body Measurement using Computer Vision & Media Pipe", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. pph152-h158, March-2025, Available at : http://www.jetir.org/papers/JETIR2503719.pdf

Publication Details

Published Paper ID: JETIR2503719
Registration ID: 557873
Published In: Volume 12 | Issue 3 | Year March-2025
DOI (Digital Object Identifier):
Page No: h152-h158
Country: Hyderabad, Telangana, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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