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Conference proceeding
AG-ReID 2023: Aerial-Ground Person Re-identification Challenge Results
2023 IEEE International Joint Conference on Biometrics (IJCB), pp 1-10
01 Jan 2023
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Person re-identification (Re-ID) on aerial-ground platforms has emerged as an intriguing topic within computer vision, presenting a plethora of unique challenges. Highflying altitudes of aerial cameras make persons appear differently in terms of viewpoints, poses, and resolution compared to the images of the same person viewed from ground cameras. Despite its potential, few algorithms have been developed for person re-identification on aerial-ground data, mainly due to the absence of comprehensive datasets. In response, we have collected a large-scale dataset and organized the Aerial-Ground person Re-IDentification Challenge (AG-ReID2023) to foster advancements in the field. The dataset comprises 100,502 images with 1,615 unique identities, including 51,530 training images featuring 807 identities. The test set is divided into two subsets: Aerial to Ground (808 ids, 4,348 query images, 19,259 gallery images) and Ground to Aerial (808 ids, 4,151 query images, 21,214 gallery images). In addition, we manually annotate individuals with their matching IDs across cameras and provide 15 soft attribute labels. The AG-ReID2023 Challenge in conjunction with the 7 th IEEE International Joint Conference on Biometrics (IJCB) has garnered interest from numerous institutes, resulting in the submission of five distinct algorithms. We provide an in-depth examination of the evaluation outcomes and present our findings from the contest. For additional details, kindly refer to the official website 1 . 1 https://agreid23.github.io.
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Details
- Title
- AG-ReID 2023: Aerial-Ground Person Re-identification Challenge Results
- Creators
- Kien Nguyen - Queensland University of TechnologyClinton Fookes - Queensland University of TechnologySridha Sridharan - Queensland University of TechnologyFeng Liu - Drexel University, Computer ScienceXiaoming Liu - Michigan State UniversityArun Ross - Michigan State UniversityDana Michalski - Defence Science and Technology GroupHuy Nguyen - Queensland University of TechnologyDebayan Deb - LENS Corporation,MI,USAMahak Kothari - LENS Corporation,MI,USAManisha Saini - LENS Corporation,MI,USADawei Du - Kitware (United States)Scott McCloskey - Kitware (United States)Gabriel Bertocco - University of Colorado Colorado SpringsFernanda Andalo - Universidade Estadual de Campinas (UNICAMP)Terrance E. Boult - University of Colorado Colorado SpringsAnderson Rocha - Universidade Estadual de Campinas (UNICAMP)Haidong Zhu - University of Southern CaliforniaZhaoheng Zheng - University of Southern CaliforniaRam Nevatia - University of Southern CaliforniaZaigham Randhawa - West Virginia UniversitySinan Sabri - University of MisanGianfranco Doretto - West Virginia University
- Publication Details
- 2023 IEEE International Joint Conference on Biometrics (IJCB), pp 1-10
- Publisher
- IEEE
- Number of pages
- 10
- Grant note
- National Science Foundation (10.13039/100000001)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:001180818700035
- Scopus ID
- 2-s2.0-85187545802
- Other Identifier
- 991022008295904721
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- Collaboration types
- Industry collaboration
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Imaging Science & Photographic Technology