{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T19:38:16Z","timestamp":1790019496660,"version":"4.0.1"},"reference-count":34,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T00:00:00Z","timestamp":1778544000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Study on Behavior Monitoring of Giant Salamanders in Zhongjian River Giant Salamander National Nature Reserve, Xianfeng County, Hubei Province","award":["2024WA064"],"award-info":[{"award-number":["2024WA064"]}]},{"name":"Research on the System Project of Monitoring and Analyzing Giant Salamander Behavior Rhythms Based on Multimodal Data","award":["XF2024070301DN"],"award-info":[{"award-number":["XF2024070301DN"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Animals"],"abstract":"<jats:p>To address the challenges posed by traditional tracking algorithms in adapting to complex underwater environments characterized by nonlinear motion, drastic morphological changes, mimicry camouflage, and frequent occlusions in wild Chinese giant salamanders, this study proposes a multi-object tracking and behavior analysis method based on the TransTrack-OC-SORT algorithm. The algorithm employs a dual-branch Transformer motion predictor to replace linear Kalman filtering, effectively capturing nonlinear motion patterns such as velocity changes and directional turns exhibited by salamanders. Simultaneously, it introduces the BIOU matching metric, which integrates center distance and aspect ratio penalties with overlap degree, thereby enhancing the robustness of associations in scenarios involving occlusion and mimicry camouflage. The results indicate that the multi-object tracking accuracy (MOTA) based on the TransTrack-OC-SORT algorithm reaches 80.9%, while the identity preservation metric (IDF1) achieves 83.7%. Quantitative behavioral analysis based on continuous trajectory data obtained from this algorithm revealed significant diurnal behavioral rhythms in the Chinese giant salamander. During the daytime, stationary behavior accounted for 95.5% of the total behavioral duration, while swimming for ventilation and foraging behaviors constituted only 4.1% and 0.4%, respectively. At night, the salamander\u2019s behavioral patterns underwent fundamental changes; although stationary behavior remained dominant (approximately 72.6%), the proportions of swimming for ventilation and foraging behaviors significantly increased to 15.1% and 12.3% of the nocturnal period, respectively. These findings enhance our understanding of the salamander\u2019s ecological habits from the perspectives of visual adaptation, energy allocation, and predation strategies. This study provides a reliable technical tool for non-invasive behavioral monitoring and rhythm research in endangered amphibians.<\/jats:p>","DOI":"10.3390\/ani16101479","type":"journal-article","created":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T12:33:37Z","timestamp":1778589217000},"page":"1479","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Underwater Multi-Target Tracking and Behavioral Rhythm Analysis of Chinese Giant Salamander Based on TransTrack-OC-SORT"],"prefix":"10.3390","volume":"16","author":[{"given":"Nanqing","family":"Sun","sequence":"first","affiliation":[{"name":"School of Intelligent Science and Engineering, Hubei Minzu University, Enshi 445000, China"},{"name":"Key Laboratory of Green Manufacturing of Super-Light Elastomer Materials, State Ethnic Affairs Commission, Hubei Minzu University, Enshi 445000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-7796-4679","authenticated-orcid":false,"given":"Xinyao","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Intelligent Science and Engineering, Hubei Minzu University, Enshi 445000, China"},{"name":"Key Laboratory of Green Manufacturing of Super-Light Elastomer Materials, State Ethnic Affairs Commission, Hubei Minzu University, Enshi 445000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mokai","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Intelligent Science and Engineering, Hubei Minzu University, Enshi 445000, China"},{"name":"Key Laboratory of Green Manufacturing of Super-Light Elastomer Materials, State Ethnic Affairs Commission, Hubei Minzu University, Enshi 445000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haotian","family":"Qian","sequence":"additional","affiliation":[{"name":"School of Intelligent Science and Engineering, Hubei Minzu University, Enshi 445000, China"},{"name":"Key Laboratory of Green Manufacturing of Super-Light Elastomer Materials, State Ethnic Affairs Commission, Hubei Minzu University, Enshi 445000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junyi","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Intelligent Science and Engineering, Hubei Minzu University, Enshi 445000, China"},{"name":"Key Laboratory of Green Manufacturing of Super-Light Elastomer Materials, State Ethnic Affairs Commission, Hubei Minzu University, Enshi 445000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3586","DOI":"10.3390\/s90503586","article-title":"Monitoring animal behaviour and environmental interactions using wireless sensor networks, GPS collars and satellite remote sensing","volume":"9","author":"Handcock","year":"2009","journal-title":"Sensors"},{"key":"ref_2","first-page":"601","article-title":"Techniques for recording the Eagle Owl (Bubo bubo) based on vocal activity","volume":"96","author":"Andreychev","year":"2017","journal-title":"Zool. Zhurnal"},{"key":"ref_3","first-page":"154","article-title":"Monitoring wildlife disease","volume":"369","author":"Alderton","year":"2020","journal-title":"Science"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Mazzamuto, M.V., Schilling, A., and Romeo, C. (2022). Wildlife disease monitoring: Methods and perspectives. Animals, 12.","DOI":"10.3390\/ani12213032"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"990","DOI":"10.1126\/science.abb0926","article-title":"Brazilian national parks at risk","volume":"367","author":"Ruaro","year":"2020","journal-title":"Science"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1038\/d41586-022-00564-y","article-title":"Protector of giant salamander","volume":"603","author":"Tay","year":"2022","journal-title":"Nature"},{"key":"ref_7","first-page":"60","article-title":"Population dynamics and conservation strategies of the Chinese giant salamander in Zhangjiajie Giant Salamander National Nature Reserve, Hunan","volume":"33","author":"Tian","year":"2025","journal-title":"Biodivers. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"111151","DOI":"10.1016\/j.compag.2025.111151","article-title":"Depth-OC-SORT-based multi-object tracking of cattle in real-world farming scenarios","volume":"240","author":"Zhu","year":"2026","journal-title":"Comput. Electron. Agric."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"126764","DOI":"10.1016\/j.eswa.2025.126764","article-title":"AppleYOLO: Apple yield estimation method using improved YOLOv8 based on Deep OC-SORT","volume":"272","author":"Tan","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"742887","DOI":"10.1016\/j.aquaculture.2025.742887","article-title":"Enhanced deep OC-SORT with YOLOv8-seg for robust fry tracking and behavior analysis in aquaculture","volume":"610","author":"Xi","year":"2026","journal-title":"Aquaculture"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"109727","DOI":"10.1016\/j.compag.2024.109727","article-title":"Estimation of passion fruit yield based on YOLOv8n+ OC-SORT+ CRCM algorithm","volume":"229","author":"Tu","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"ref_12","first-page":"475","article-title":"Multi-object tracking method for sheep fusing depth information and motion trends","volume":"56","author":"Wang","year":"2025","journal-title":"Trans. Chin. Soc. Agric. Mach."},{"key":"ref_13","unstructured":"Chen, H., Liu, G., Hu, C., and Zhang, X. (2026). Dense pedestrian detection and tracking method based on feature fusion in complex traffic environments. Comput. Eng. Appl., 1\u201316. Available online: https:\/\/link.cnki.net\/urlid\/11.2127.TP.20251231.1529.011."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Ferreira, D., and Basiri, M. (2024). Dynamic target tracking and following with UAVs using multi-target information: Leveraging YOLOv8 and MOT algorithms. Drones, 8.","DOI":"10.3390\/drones8090488"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1007\/s00138-023-01398-y","article-title":"VGT-MOT: Visibility-guided tracking for online multiple-object tracking","volume":"34","author":"Wang","year":"2023","journal-title":"Mach. Vis. Appl."},{"key":"ref_16","first-page":"7","article-title":"Multi-object tracking algorithm based on unscented Kalman filter in SORT framework","volume":"46","author":"Chen","year":"2025","journal-title":"Guid. Fuze"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Hong, J., Li, Y., Yan, J., Wei, X., Xian, W., and Qin, Y. (2025). KalmanFormer: Integrating a deep motion model into SORT for video multi-object tracking. Appl. Sci., 15.","DOI":"10.3390\/app15179727"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"111091","DOI":"10.1016\/j.patcog.2024.111091","article-title":"Seatrack: Rethinking observation-centric sort for robust nearshore multiple object tracking","volume":"159","author":"Ding","year":"2025","journal-title":"Pattern Recognit."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Shen, P., Mei, K., Xue, H., Li, T., Zhang, G., Zhao, Y., Luo, W., and Mao, L. (2025). Research on enhanced dynamic pig counting based on YOLOv8n and Deep SORT. Sensors, 25.","DOI":"10.3390\/s25092680"},{"key":"ref_20","unstructured":"Hu, X., Shao, L., Zhou, Y., Xiao, J., and Cheng, H. (2026). Remote small target vehicle detection and tracking algorithm based on improved YOLOv5s-CSC and Deep-Sort. J. Southwest Jiaotong Univ., 1\u201313. Available online: https:\/\/link.cnki.net\/urlid\/51.1277.u.20250311.1634.012."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"107339","DOI":"10.1016\/j.compag.2022.107339","article-title":"Multi-object tracking using Deep SORT and modified CenterNet in cotton seedling counting","volume":"202","author":"Yang","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"ref_22","first-page":"127","article-title":"Inspection and counting method of greenhouse tomato fruits based on improved YOLO v8n-ByteTrack","volume":"57","author":"Feng","year":"2026","journal-title":"Trans. Chin. Soc. Agric. Mach."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"You, L., Chen, Y., Xiao, C., Sun, C., and Li, R. (2024). Multi-object vehicle detection and tracking algorithm based on improved YOLOv8 and ByteTrack. Electronics, 13.","DOI":"10.3390\/electronics13153033"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Tu, S., Ou, H., Mao, L., Du, J., Cao, Y., and Chen, W. (2024). Behavior tracking and analyses of group-housed pigs based on improved ByteTrack. Animals, 14.","DOI":"10.3390\/ani14223299"},{"key":"ref_25","first-page":"110","article-title":"Research on giant salamander detection model based on improved YOLO 11n-EWL","volume":"56","author":"Tian","year":"2025","journal-title":"Trans. Chin. Soc. Agric. Mach."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Sun, N., Lu, D., Yang, X., Gao, H., and Chen, J. (2025). Study on the localization technology for giant salamanders using passive UHF RFID and incomplete D-Tr measurement data. Sensors, 26.","DOI":"10.22541\/au.175731685.54473421\/v1"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Walls, S.C., and Gabor, C.R. (2019). Integrating behavior and physiology into strategies for amphibian conservation. Front. Ecol. Evol., 7.","DOI":"10.3389\/fevo.2019.00234"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1007\/s10530-019-02181-9","article-title":"A subtle threat: Behavioral and phenotypic consequences of invasive mosquitofish on a native paedomorphic newt","volume":"22","author":"Toli","year":"2020","journal-title":"Biol. Invasions"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Mohun, S.M., and Davies, W.I.L. (2019). The evolution of amphibian photoreception. Front. Ecol. Evol., 7.","DOI":"10.3389\/fevo.2019.00321"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"101819","DOI":"10.1016\/j.psj.2022.101819","article-title":"Effects of different light intensities on the transcriptome changes of duck retina and pineal gland","volume":"101","author":"Qi","year":"2022","journal-title":"Poult. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Benedetto, M.M., Guido, M.E., and Contin, M.A. (2017). Non-visual photopigments effects of constant light-emitting diode light exposure on the inner retina of Wistar rats. Front. Neurol., 8.","DOI":"10.3389\/fneur.2017.00417"},{"key":"ref_32","unstructured":"Cao, J., Deng, Z., Jiang, W., Li, H., Wang, C., Xie, Y., Zhou, S., Xiang, H., and Wei, Y. (2026). Fish diversity in Zhangjiajie Giant Salamander National Nature Reserve, Hunan. J. Hydroecol., 1\u201318."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"102658","DOI":"10.1016\/j.aquaeng.2025.102658","article-title":"Angle-aware multi-object fish tracking with unique forward orientation estimation","volume":"112","author":"Li","year":"2025","journal-title":"Aquac. Eng."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"112552","DOI":"10.1016\/j.dib.2026.112552","article-title":"An annotated dataset of images of Chinese giant salamanders","volume":"65","author":"Yang","year":"2026","journal-title":"Data Brief"}],"container-title":["Animals"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-2615\/16\/10\/1479\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T13:19:46Z","timestamp":1778591986000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-2615\/16\/10\/1479"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,12]]},"references-count":34,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2026,5]]}},"alternative-id":["ani16101479"],"URL":"https:\/\/doi.org\/10.3390\/ani16101479","relation":{},"ISSN":["2076-2615"],"issn-type":[{"value":"2076-2615","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,12]]}}}