Smart City Gnosys
Smart city article details
| Title | A Review On Person Re-Identification Techniques And Its Analysis |
|---|---|
| ID_Doc | 4278 |
| Authors | Selvan C.; Anwar Basha H.; Meenakshi K.; Naveen S. |
| Year | 2025 |
| Published | IEEE Access, 13 |
| DOI | http://dx.doi.org/10.1109/ACCESS.2025.3536478 |
| Abstract | Person re-identification (Re-ID) emerges as a captivating realm within computer vision, dedicated to the task of recognizing the same individual across diverse camera angles or locations. The realm of video-based person re-identification (video re-ID) has recently captivated increasing interest, owing to its wide array of practical applications spanning surveillance, smart city solutions, and public safety measures. Nevertheless, video re-ID proves to be a formidable challenge, an ever-evolving domain fraught with a multitude of uncertainties like viewpoint variations, occlusions, pose changes, and unpredictable video sequences. Over the past few years, the realm of deep learning applied to video re-ID has consistently delivered remarkable outcomes on public datasets, showcasing a range of innovative strategies devised to tackle the array of issues encountered in video re-ID. In stark contrast to image-based re-ID, video re-ID stands out as significantly more intricate and demanding. In a bid to inspire forthcoming research endeavors and confronts emerging challenges, this paper presents a comprehensive overview of the latest advancements in deep learning methodologies tailored for video re-ID. It delves into three crucial facets; encompassing succinct explanations of video re-ID techniques along with their constraints, pivotal breakthroughs coupled with the technical hurdles faced, and the architectural framework underpinning these developments. The paper further furnishes a comparative analysis of performance across diverse datasets, offers insightful guidance on enhancing video re-ID strategies, and outlines compelling avenues for future research exploration. © 2013 IEEE. |
| Author Keywords | deep learning; Person re-identification; review analysis; vision based re-identification |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
30088  | 0.925 | Qian Y.; Barthelemy J.; Karuppiah E.; Perez P. | Identifying Re-Identification Challenges: Past, Current And Future Trends | SN Computer Science, 5, 7 (2024) |
| 5185 | 0.922 | Li Q.; Hu W.-Y.; Li J.-Y.; Liu Y.; Li M.-X. | A Survey Of Person Re-Identification Based On Deep Learning; [基于深度学习的行人重识别方法综述] | Gongcheng Kexue Xuebao/Chinese Journal of Engineering, 44, 5 (2022) |
| 7827 | 0.912 | Maqsood M.; Yasmin S.; Gillani S.; Bukhari M.; Rho S.; Yeo S.-S. | An Efficient Deep Learning-Assisted Person Re-Identification Solution For Intelligent Video Surveillance In Smart Cities | Frontiers of Computer Science, 17, 4 (2023) |
| 51477 | 0.911 | Perwaiz N.; Fraz M.M.; Shahzad M. | Smart Surveillance With Simultaneous Person Detection And Re-Identification | Multimedia Tools and Applications, 83, 5 (2024) |
| 44581 | 0.904 | Zhang Y.; Yang H.; Zhang Y.; Dou Z.; Liao S.; Zheng W.; Zhang S.; Ye M.; Yan Y.; Li J.; Wang S. | Recent Progress In Person Re-Id; [行人再识别技术研究进展] | Journal of Image and Graphics, 28, 6 (2023) |
| 27017 | 0.897 | Zhuang J.; Wang N.; Zhuang Y.; Hao Y. | Frame Extraction Person Retrieval Framework Based On Improved Yolov8S And The Stage-Wise Clustering Person Re-Identification | IET Image Processing, 19, 1 (2025) |
| 10212 | 0.894 | Mamedov T.; Kuplyakov D.; Konushin A. | Approaches To Improve The Quality Of Person Re-Identification For Practical Use | Sensors, 23, 17 (2023) |
| 41889 | 0.894 | Qi L.; Ren Z.; Liu J.; Geng X. | Person Re-Identification Method Based On Hybrid Real-Synthetic Data; [虚实结合的行人重识别方法] | Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 62, 2 (2025) |
| 18110 | 0.891 | Khan S.U.; Hussain T.; Ullah A.; Baik S.W. | Deep-Reid: Deep Features And Autoencoder Assisted Image Patching Strategy For Person Re-Identification In Smart Cities Surveillance | Multimedia Tools and Applications, 83, 5 (2024) |
| 7876 | 0.89 | Wang Z.; Luo S.; Sun H.; Pan H.; Yin J. | An Efficient Non-Local Attention Network For Video-Based Person Re-Identification | ACM International Conference Proceeding Series (2019) |