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Due to these correlations being capable of being efficiently computed in a Fourier domain by discrete Fourier transform (DFT), the DFT of an image has symmetry in the Fourier domain. However, DCF tracking methods easily generate unwanted boundary effects where the tracking object suffers from challenging situations, such as deformation, fast motion and occlusion. To tackle the above issue, this work proposes a novel saliency-aware and spatial\u2013temporal regularized correlation filter (SSTCF) model for visual object tracking. First, the introduced spatial\u2013temporal regularization helps build a more robust correlation filter (CF) and improve the temporal continuity and consistency of the model to effectively lower boundary effects and enhance tracking performance. In addition, the relevant objective function can be optimized into three closed-form subproblems which can be addressed by using the alternating direction method of multipliers (ADMM) competently. Furthermore, utilizing a saliency detection method to acquire a saliency-aware weight enables the tracker to adjust to variations in appearance and mitigate disturbances from the surroundings environment. Finally, we conducted numerous experiments based on three different benchmarks, and the results showed that our proposed model had better performance and higher efficiency compared to the most advanced trackers. For example, the distance precision (DP) score was 0.883, and the area under the curve (AUC) score was 0.676 on the OTB2015 dataset.<\/jats:p>","DOI":"10.3390\/sym16081076","type":"journal-article","created":{"date-parts":[[2024,8,20]],"date-time":"2024-08-20T06:07:35Z","timestamp":1724134055000},"page":"1076","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["UAV Tracking via Saliency-Aware and Spatial\u2013Temporal Regularization Correlation Filter Learning"],"prefix":"10.3390","volume":"16","author":[{"given":"Liqiang","family":"Liu","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Xi\u2019an Technological University, Xi\u2019an 710021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6392-1235","authenticated-orcid":false,"given":"Tiantian","family":"Feng","sequence":"additional","affiliation":[{"name":"Science and Technology on Electromechanical Control Laboratory, Xi\u2019an 710065, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanfang","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Xi\u2019an Technological University, Xi\u2019an 710021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingling","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Xi\u2019an Technological University, Xi\u2019an 710021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongmei","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Xi\u2019an Technological University, Xi\u2019an 710021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zijian","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Xi\u2019an Technological University, Xi\u2019an 710021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1145\/1177352.1177355","article-title":"Object tracking: A survey","volume":"38","author":"Yilmaz","year":"2006","journal-title":"ACM Comput. 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