{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:11:22Z","timestamp":1760105482606,"version":"build-2065373602"},"reference-count":64,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2024,1,3]],"date-time":"2024-01-03T00:00:00Z","timestamp":1704240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62272423","62072416","62102373","62006213","21HASTIT028","202300410495"],"award-info":[{"award-number":["62272423","62072416","62102373","62006213","21HASTIT028","202300410495"]}]},{"name":"Program for Science &amp; Technology Innovation Talents in Universities of Henan Province, China","award":["62272423","62072416","62102373","62006213","21HASTIT028","202300410495"],"award-info":[{"award-number":["62272423","62072416","62102373","62006213","21HASTIT028","202300410495"]}]},{"name":"Natural Science Foundation of Henan Province, China","award":["62272423","62072416","62102373","62006213","21HASTIT028","202300410495"],"award-info":[{"award-number":["62272423","62072416","62102373","62006213","21HASTIT028","202300410495"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Siamese trackers based on classification and regression have drawn extensive attention due to their appropriate balance between accuracy and efficiency. However, most of them are prone to failure in the face of abrupt motion or appearance changes. This paper proposes a Siamese-based tracker that incorporates spatial-semantic-aware attention and flexible spatiotemporal constraint. First, we develop a spatial-semantic-aware attention model, which identifies the importance of each feature region and channel to target representation through the single convolution attention network with a loss function and increases the corresponding weights in the spatial and channel dimensions to reinforce the target region and semantic information on the target feature map. Secondly, considering that the traditional method unreasonably weights the target response in abrupt motion, we design a flexible spatiotemporal constraint. This constraint adaptively adjusts the constraint weights on the response map by evaluating the tracking result. Finally, we propose a new template updating the strategy. This strategy adaptively adjusts the contribution weights of the tracking result to the new template using depth correlation assessment criteria, thereby enhancing the reliability of the template. The Siamese network used in this paper is a symmetric neural network with dual input branches sharing weights. The experimental results on five challenging datasets show that our method outperformed other advanced algorithms.<\/jats:p>","DOI":"10.3390\/sym16010061","type":"journal-article","created":{"date-parts":[[2024,1,3]],"date-time":"2024-01-03T03:18:07Z","timestamp":1704251887000},"page":"61","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Siamese Tracking Network with Spatial-Semantic-Aware Attention and Flexible Spatiotemporal Constraint"],"prefix":"10.3390","volume":"16","author":[{"given":"Huanlong","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Panyun","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fengxian","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1493-0308","authenticated-orcid":false,"given":"Xiaohui","family":"Song","sequence":"additional","affiliation":[{"name":"Henan Academy of Science, Zhengzhou 450008, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hebin","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.engappai.2016.10.016","article-title":"Vision-based control of a quadrotor utilizing artificial neural networks for tracking of moving targets","volume":"58","author":"Shirzadeh","year":"2017","journal-title":"Eng. 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