{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T12:01:14Z","timestamp":1775217674335,"version":"3.50.1"},"reference-count":32,"publisher":"Institution of Engineering and Technology (IET)","issue":"1","license":[{"start":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T00:00:00Z","timestamp":1753142400000},"content-version":"vor","delay-in-days":202,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFF1302700"],"award-info":[{"award-number":["2022YFF1302700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["QNTD202504"],"award-info":[{"award-number":["QNTD202504"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["ietresearch.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["IET Image Processing"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>The conservation of endangered species is contingent upon accurate and efficient wildlife monitoring, which is essential for informed decision\u2010making and effective preservation strategies. With the global population of Amur tigers (Panthera tigris altaica) falling below 600, innovative conservation strategies are critically needed. Traditional monitoring methods have fallen short in accuracy and efficiency, leading to a shift towards leveraging big data and artificial intelligence for effective wildlife surveillance. Existing re\u2010identification techniques struggle with natural habitat challenges like occlusions, changing poses, varying light, and limited data. To overcome these issues, we propose the pose\u2010guided dual branch re\u2010identification network (PDBRNet). Our approach integrates pose estimation to guide feature disentanglement and alignment, crucial for accurate re\u2010identification, while an image preprocessing method considering illumination factors mitigates lighting variations' impact on accuracy. Through validation on the occluded and illumination\u2010varying amur tiger (OIAT) dataset, PDBRNet demonstrates exceptional performance. Specifically, in single\u2010camera scenarios, PDBRNet achieves an outstanding mean average precision (mAP) of 79.4, surpassing the performance of PGCFL (51.6) and PPGNet (69.7). Moreover, in cross\u2010camera scenarios, PDBRNet maintains its superiority with a remarkable mAP of 54.0, along with Rank\u20101 and Rank\u20105 scores of 97.8 and 98.9, respectively, showcasing its robustness in real\u2010world surveillance applications. The introduction of PDBRNet significantly enhances re\u2010identification accuracy and holds promise for addressing complexities in field environments, contributing significantly to wildlife conservation\u00a0efforts.<\/jats:p>","DOI":"10.1049\/ipr2.70160","type":"journal-article","created":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T07:44:44Z","timestamp":1753170284000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Pose\u2010Guided Re\u2010Identification of Amur Tigers Under Wild Environmental Constraints"],"prefix":"10.1049","volume":"19","author":[{"given":"Tianyu","family":"Wang","sequence":"first","affiliation":[{"name":"School of Information Science and Technology (School of Artificial Intelligence) Beijing Forestry University Beijing China"},{"name":"Engineering Research Center for Forestry\u2010Oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing China"},{"name":"Hebei Key Laboratory of Smart National Park Beijing China"}]},{"given":"Boxuan","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology (School of Artificial Intelligence) Beijing Forestry University Beijing China"},{"name":"Engineering Research Center for Forestry\u2010Oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing China"},{"name":"Hebei Key Laboratory of Smart National Park Beijing China"}]},{"given":"Xinrui","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology (School of Artificial Intelligence) Beijing Forestry University Beijing China"},{"name":"Engineering Research Center for Forestry\u2010Oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing China"},{"name":"Hebei Key Laboratory of Smart National Park Beijing China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9503-972X","authenticated-orcid":false,"given":"Chao","family":"Mou","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology (School of Artificial Intelligence) Beijing Forestry University Beijing China"},{"name":"Engineering Research Center for Forestry\u2010Oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing China"},{"name":"Hebei Key Laboratory of Smart National Park Beijing China"}]},{"given":"Jiahua","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology (School of Artificial Intelligence) Beijing Forestry University Beijing China"},{"name":"Engineering Research Center for Forestry\u2010Oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing China"},{"name":"Hebei Key Laboratory of Smart National Park Beijing China"}]}],"member":"265","published-online":{"date-parts":[[2025,7,22]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10592-004-1860-2"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-294X.2009.04266.x"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1128\/mBio.00410-13"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2000153117"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolind.2025.113227"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1644\/12-MAMM-A-209.1"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.24189\/ncr.2016.025"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecoinf.2022.101947"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12686-015-0476-9"},{"key":"e_1_2_11_11_1","doi-asserted-by":"crossref","unstructured":"Y.Xia Y.Hu W.Liu andT.Que \u201cResearch on Re\u2010Identification of Amur Tigers and Bengal Tigers \u201d in2024 2nd International Conference on Big Data and Privacy Computing (BDPC)(IEEE 2024) 141\u2013147.","DOI":"10.1109\/BDPC59998.2024.10649232"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.3390\/ani14071106"},{"key":"e_1_2_11_13_1","doi-asserted-by":"crossref","unstructured":"V.\u010cerm\u00e1k L.Picek L.Adam andK.Papafitsoros \u201cWildlifeDatasets: An Open\u2010Source Toolkit for Animal Re\u2010Identification \u201d inProceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision(2024) 5953\u20135963.","DOI":"10.1109\/WACV57701.2024.00585"},{"key":"e_1_2_11_14_1","doi-asserted-by":"crossref","unstructured":"X.Bai T.Islam M. 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B.Azhar \u201cTransformer\u2010Based Models for Enhanced Amur Tiger Re\u2010Identification \u201d in2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI)(IEEE 2024) 000411\u2013000416.","DOI":"10.1109\/SAMI60510.2024.10432893"},{"key":"e_1_2_11_15_1","doi-asserted-by":"crossref","unstructured":"S.Li J.Li H.Tang R.Qian andW.Lin \u201cATRW: A Benchmark for Amur Tiger Re\u2010Identification in the Wild \u201darXiv preprint arXiv:1906.05586(2019).","DOI":"10.1145\/3394171.3413569"},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.1111\/2041-210X.13133"},{"key":"e_1_2_11_17_1","doi-asserted-by":"crossref","unstructured":"X.Cheng J.Zhu N.Zhang Q.Wang andQ.Zhao \u201cDetection Features as Attention (Defat): A Keypoint\u2010Free Approach to Amur Tiger Re\u2010Identification \u201d in2020 IEEE International Conference on Image Processing (ICIP)(IEEE 2020) 2231\u20132235.","DOI":"10.1109\/ICIP40778.2020.9190667"},{"key":"e_1_2_11_18_1","doi-asserted-by":"crossref","unstructured":"A.Shukla G. 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