Facial Recognition and Feature Mapping with Machine Learning

G. Prathibha Priyadarshini, G. Utejitha, D. Tejaswini, K. Swathi, A. Renuka

2025

Abstract

Facial recognition and machine learning-based feature mapping have become key security, authentication, and human-computer interaction technologies. This research discusses the application of deep learning-based facial recognition systems that map and analyze facial features to perform robust identification and verification. The system utilizes convolutional neural networks (CNNs) to extract and classify features for enhanced accuracy and the ability to counter light, pose, and occlusion variations. Feature mapping methods like key point detection and embedding generation facilitate effective face matching and identification. The approach improves security, reduces and embedding generation facilitate effective face matching and identification. The approach improves security, reduces false positives, and offers a scalable solution for real-time surveillance, biometric, and personalized user experience applications. Experimental results prove the model's effectiveness in delivering high recognition accuracy with optimized computational efficiency.

Paper Citation

in Harvard Style

Priyadarshini G., Utejitha G., Tejaswini D., Swathi K. and Renuka A. (2025). Facial Recognition and Feature Mapping with Machine Learning. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 478-484. DOI: 10.5220/0013867900004919

in Bibtex Style

@conference{icrdicct`2525,
author={G. Prathibha Priyadarshini and G. Utejitha and D. Tejaswini and K. Swathi and A. Renuka},
title={Facial Recognition and Feature Mapping with Machine Learning},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25},
year={2025},
pages={478-484},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013867900004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25
TI - Facial Recognition and Feature Mapping with Machine Learning
SN - 978-989-758-777-1
AU - Priyadarshini G.
AU - Utejitha G.
AU - Tejaswini D.
AU - Swathi K.
AU - Renuka A.
PY - 2025
SP - 478
EP - 484
DO - 10.5220/0013867900004919
PB - SciTePress