A Brief Overview on Deep Learning-Based Person Re-Identification

Person re-identification (Re-ID) has attracted considerable attention within the field of biometrics in recent times, driven by an escalating demand in public communities, marketing and banking endeavors, and social media networks. Moreover, the rapid advancement of deep learning has introduced a wide range of effective tools for addressing person re-identification tasks. The result is more precise and faster processing compared to the video surveillance performed manually by human operators. This article provides an overview of recent Re-ID studies by highlighting the challenges and issues, proposing a taxonomy of Re-ID methods, and comparing the performances of the most representative deep learning-based approaches.