Person Re-Identification From Video Surveillance Systems Using Artificial Intelligence Methods
- 1 Department of Computer Science & Systems Engineering, Andhra University College of Engineering, Waltair, India
Abstract
The study explores use of deep learning models in person re identification, leveraging the advancements made in face recognition however the abundance of model choices presents a challenge in selecting the optimal architecture. The study proposes a comprehensive framework for evaluating deep learning models on person re-identification tasks by considering various performance metrics, dataset preprocessing methods, model architectures, and evaluation techniques to enable a systematic comparison of different approaches through empirical analyses on standard person re-identification datasets. The proposed framework is worked-out in uncovering the strengths and limitations of diverse deep learning strategies. The primary objective is to utilize face recognition methodologies to achieve accurate person re-identification.
DOI: https://doi.org/10.3844/jcssp.2025.1819.1833
Copyright: © 2025 Revathi Lavanya Baggam and Vatsavayi Valli Kumari. 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.
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Keywords
- Deep Learning (DL)
- Machine Learning (ML)
- Face Recognition (FR)
- Mathematical Model
- Model Comparison
- Performance Metrics
- Dataset Preprocessing
- Model Architecture
- Evaluation Methodology