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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM17000

DEPTH MEASUREMENT OF HUMANS USING WEB CAM

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM17000

Volume:

7 |

1 |

Jan 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

DCKG

Dr. C K Gomathy

DVG

Dr. V Geetha

ASR

A. Srinivas Reddy

AUK

A Uday Kiran

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Abstract

Artificial Intelligence has gradually become the mainstream in the detection algorithms because of its powerful feature extraction ability and adaptive ability. However, how to guarantee the accuracy and speed is still a huge challenge in the field of depth measurement. We implement face mesh from media pipe (module) which is developed by google. Media Pipe Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices. It employs machine learning (ML) to infer the 3D surface geometry, requiring a single camera input without the need for a dedicated depth sensor. Using face mesh, we take points from face and depth is measured. This makes project more accurate and speed. In our project we measure real time 3D depth, using these we make our text flexible with depth measured from webcam. When we move closer to our webcam text size reduces, and when we go far from webcam, text size is enhanced, which is accordance to the convenience to our end users. When we implement this in real life, end users can see the captions comfortably from any place they are watching the screen only.

KEYWORDS

OpenCV Mediapipe FaceMesh Windows Python.

Cite This Article

Dr. C K Gomathy, Dr. V Geetha, A. Srinivas Reddy, A Uday Kiran, "DEPTH MEASUREMENT OF HUMANS USING WEB CAM," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 1, Jan 2023. https://doi.org/10.55041/IJSREM17000

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Publication Date

2/28/2023

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Double-Blind Peer Review

Review Rounds: 2

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0

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22

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5

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The authors declare no conflict of interest related to this research work.

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