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Xu N, Ma Z, Xia Y, Dong Y, Zi J, Xu D, Xu F, Su X, Zhang H, Chen F. A Serial Multi-Scale Feature Fusion and Enhancement Network for Amur Tiger Re-Identification. Animals (Basel) 2024; 14:1106. [PMID: 38612345 PMCID: PMC11011027 DOI: 10.3390/ani14071106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 03/26/2024] [Accepted: 04/02/2024] [Indexed: 04/14/2024] Open
Abstract
The Amur tiger is an important endangered species in the world, and its re-identification (re-ID) plays an important role in regional biodiversity assessment and wildlife resource statistics. This paper focuses on the task of Amur tiger re-ID based on visible light images from screenshots of surveillance videos or camera traps, aiming to solve the problem of low accuracy caused by camera perspective, noisy background noise, changes in motion posture, and deformation of Amur tiger body patterns during the re-ID process. To overcome this challenge, we propose a serial multi-scale feature fusion and enhancement re-ID network of Amur tiger for this task, in which global and local branches are constructed. Specifically, we design a global inverted pyramid multi-scale feature fusion method in the global branch to effectively fuse multi-scale global features and achieve high-level, fine-grained, and deep semantic feature preservation. We also design a local dual-domain attention feature enhancement method in the local branch, further enhancing local feature extraction and fusion by dividing local feature blocks. Based on the above model structure, we evaluated the effectiveness and feasibility of the model on the public dataset of the Amur Tiger Re-identification in the Wild (ATRW), and achieved good results on mAP, Rank-1, and Rank-5, demonstrating a certain competitiveness. In addition, since our proposed model does not require the introduction of additional expensive annotation information and does not incorporate other pre-training modules, it has important advantages such as strong transferability and simple training.
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Affiliation(s)
- Nuo Xu
- School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China; (N.X.); (Z.M.); (Y.X.); (Y.D.); (J.Z.); (D.X.); (F.X.); (X.S.); (H.Z.)
| | - Zhibin Ma
- School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China; (N.X.); (Z.M.); (Y.X.); (Y.D.); (J.Z.); (D.X.); (F.X.); (X.S.); (H.Z.)
| | - Yi Xia
- School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China; (N.X.); (Z.M.); (Y.X.); (Y.D.); (J.Z.); (D.X.); (F.X.); (X.S.); (H.Z.)
| | - Yanqi Dong
- School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China; (N.X.); (Z.M.); (Y.X.); (Y.D.); (J.Z.); (D.X.); (F.X.); (X.S.); (H.Z.)
| | - Jiali Zi
- School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China; (N.X.); (Z.M.); (Y.X.); (Y.D.); (J.Z.); (D.X.); (F.X.); (X.S.); (H.Z.)
| | - Delong Xu
- School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China; (N.X.); (Z.M.); (Y.X.); (Y.D.); (J.Z.); (D.X.); (F.X.); (X.S.); (H.Z.)
| | - Fu Xu
- School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China; (N.X.); (Z.M.); (Y.X.); (Y.D.); (J.Z.); (D.X.); (F.X.); (X.S.); (H.Z.)
- Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing 100083, China
| | - Xiaohui Su
- School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China; (N.X.); (Z.M.); (Y.X.); (Y.D.); (J.Z.); (D.X.); (F.X.); (X.S.); (H.Z.)
- Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing 100083, China
| | - Haiyan Zhang
- School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China; (N.X.); (Z.M.); (Y.X.); (Y.D.); (J.Z.); (D.X.); (F.X.); (X.S.); (H.Z.)
- Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing 100083, China
| | - Feixiang Chen
- School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China; (N.X.); (Z.M.); (Y.X.); (Y.D.); (J.Z.); (D.X.); (F.X.); (X.S.); (H.Z.)
- Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing 100083, China
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Wang Y, Wei W, Yuan F, Cao D, Zhang Z. The Science Underlying Giant Panda Conservation Translocations. Animals (Basel) 2023; 13:3332. [PMID: 37958087 PMCID: PMC10649174 DOI: 10.3390/ani13213332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 10/18/2023] [Accepted: 10/24/2023] [Indexed: 11/15/2023] Open
Abstract
The giant panda (Ailuropoda melanoleuca) is the flagship species of animal conservation worldwide, and the number of captive pandas reached 673 in 2021. According to the Fourth National Survey Report on the Giant Panda, there are 1864 wild pandas, segregated into 33 local populations, and 25 of these populations are too small to be self-sustaining. In addition to the conservation and restoration of panda habitats, conservation translocations, an approach that has been shown to be effective in slowing or reversing biodiversity loss, are highly desirable for panda conservation. The captive-bred panda population has grown rapidly, laying the foundation for releasing captive-bred pandas into the wild. This paper reviews the scientific advances in conservation translocations of pandas. Studies have shown that before translocation conservation programs are implemented, we should determine what factors are causing the depletion of the original population at the release site. The selection of suitable release sites and individuals will help to improve the survival rate of released individuals in the wild. Pre-release training and post-release monitoring are essential to ensure successful releases. We also see the great potential for increasing applications of Adaptive Management to improve the success of giant panda conservation translocation programs. This review provides theoretical guidance for improvement of the success rate in conservation translocations for captive pandas, and uses the panda as a model species to provide a global reference for the conservation translocations of rare and endangered species.
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Affiliation(s)
- Yue Wang
- Key Laboratory of Southwest China Wildlife Resources Conservation (Ministry of Education), China West Normal University, Nanchong 637001, China; (Y.W.); (W.W.); (D.C.)
- Liziping Giant Panda’s Ecology and Conservation Observation and Research Station of Sichuan Province, China West Normal University, Nanchong 637001, China
| | - Wei Wei
- Key Laboratory of Southwest China Wildlife Resources Conservation (Ministry of Education), China West Normal University, Nanchong 637001, China; (Y.W.); (W.W.); (D.C.)
- Liziping Giant Panda’s Ecology and Conservation Observation and Research Station of Sichuan Province, China West Normal University, Nanchong 637001, China
| | - Feiyun Yuan
- Sichuan Lushi Expressway Co., Ltd., Chengdu 610041, China;
| | - Dandan Cao
- Key Laboratory of Southwest China Wildlife Resources Conservation (Ministry of Education), China West Normal University, Nanchong 637001, China; (Y.W.); (W.W.); (D.C.)
- Liziping Giant Panda’s Ecology and Conservation Observation and Research Station of Sichuan Province, China West Normal University, Nanchong 637001, China
| | - Zejun Zhang
- Key Laboratory of Southwest China Wildlife Resources Conservation (Ministry of Education), China West Normal University, Nanchong 637001, China; (Y.W.); (W.W.); (D.C.)
- Liziping Giant Panda’s Ecology and Conservation Observation and Research Station of Sichuan Province, China West Normal University, Nanchong 637001, China
- Chengdu Normal University, Chengdu 611130, China
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An experiment on animal re-identification from video. ECOL INFORM 2023. [DOI: 10.1016/j.ecoinf.2023.101994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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