Decentralized Text-Based Person Re-Identification in Multi-Camera Networks
Text-based person re-identification (re-ID) is an emerging research domain in multi-camera surveillance systems. It involves identifying individuals across different camera views using textual descriptions as queries. Although text-based person re-ID holds significant potential for surveillance syst...
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| Vydáno v: | IEEE access Ročník 12; s. 172125 - 172148 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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2024
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| ISSN: | 2169-3536, 2169-3536 |
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| Abstract | Text-based person re-identification (re-ID) is an emerging research domain in multi-camera surveillance systems. It involves identifying individuals across different camera views using textual descriptions as queries. Although text-based person re-ID holds significant potential for surveillance systems, its practical applications are limited by the high computational demands of existing algorithms. This is because most state-of-the-art algorithms prioritize identification accuracy over resource efficiency. Therefore, surveillance systems based on existing algorithms rely heavily on centralized architectures, where a central application server aggregates videos from camera nodes, generates galleries from the videos, and performs person identification. However, such centralized systems face challenges in large-scale deployments, including scalability issues, high bandwidth utilization, and processing bottlenecks. This paper presents a decentralized approach to text-based person re-ID to overcome these limitations. First, it introduces U-TextReIDNet, a resource-efficient model designed to identify persons in multi-person images on the NVIDIA Jetson Nano embedded board. U-TextReIDNet achieves Top-1 accuracies of 54.02% on the CUHK-PEDES dataset and 38.45% on the RSTPReid dataset. With only 38.77 million parameters, U-TextReIDNet is significantly smaller than most existing text-based person re-ID models. Using U-TextReIDNet, we implement a decentralized system that distributes the person identification task across camera nodes, transmitting only videos containing persons of interest to the command station. Additionally, we developed a prototype of this decentralized system, and conducted performance and usability tests using real human subjects. The prototype successfully performs real-time person re-ID, reduces bandwidth utilization, improves system scalability, and eliminates processing bottlenecks. |
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| AbstractList | Text-based person re-identification (re-ID) is an emerging research domain in multi-camera surveillance systems. It involves identifying individuals across different camera views using textual descriptions as queries. Although text-based person re-ID holds significant potential for surveillance systems, its practical applications are limited by the high computational demands of existing algorithms. This is because most state-of-the-art algorithms prioritize identification accuracy over resource efficiency. Therefore, surveillance systems based on existing algorithms rely heavily on centralized architectures, where a central application server aggregates videos from camera nodes, generates galleries from the videos, and performs person identification. However, such centralized systems face challenges in large-scale deployments, including scalability issues, high bandwidth utilization, and processing bottlenecks. This paper presents a decentralized approach to text-based person re-ID to overcome these limitations. First, it introduces U-TextReIDNet, a resource-efficient model designed to identify persons in multi-person images on the NVIDIA Jetson Nano embedded board. U-TextReIDNet achieves Top-1 accuracies of 54.02% on the CUHK-PEDES dataset and 38.45% on the RSTPReid dataset. With only 38.77 million parameters, U-TextReIDNet is significantly smaller than most existing text-based person re-ID models. Using U-TextReIDNet, we implement a decentralized system that distributes the person identification task across camera nodes, transmitting only videos containing persons of interest to the command station. Additionally, we developed a prototype of this decentralized system, and conducted performance and usability tests using real human subjects. The prototype successfully performs real-time person re-ID, reduces bandwidth utilization, improves system scalability, and eliminates processing bottlenecks. |
| Author | Rinner, Bernhard Agyeman, Rockson |
| Author_xml | – sequence: 1 givenname: Rockson orcidid: 0000-0001-7777-5996 surname: Agyeman fullname: Agyeman, Rockson organization: Institute of Networked and Embedded Systems, University of Klagenfurt, Klagenfurt am Wörthersee, Austria – sequence: 2 givenname: Bernhard orcidid: 0000-0002-8793-3828 surname: Rinner fullname: Rinner, Bernhard email: bernhard.rinner@aau.at organization: Institute of Networked and Embedded Systems, University of Klagenfurt, Klagenfurt am Wörthersee, Austria |
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| SubjectTerms | Accuracy Algorithms Application servers Cameras Computer architecture Datasets Decentralized algorithm Feature extraction Human performance Identification of persons multi-camera networks multi-modal re-identification model Nodes Parameter identification Privacy Prototypes Real time real-time video analytics Scalability Servers Surveillance Surveillance systems text-based person re-identification Video Videos Visualization |
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| Title | Decentralized Text-Based Person Re-Identification in Multi-Camera Networks |
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