{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T13:37:42Z","timestamp":1762522662192,"version":"build-2065373602"},"reference-count":59,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T00:00:00Z","timestamp":1643587200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Tracking moving objects is one of the most promising yet the most challenging research areas pertaining to computer vision, pattern recognition and image processing. The challenges associated with object tracking range from problems pertaining to camera axis orientations to object occlusion. In addition, variations in remote scene environments add to the difficulties related to object tracking. All the mentioned challenges and problems pertaining to object tracking make the procedure computationally complex and time-consuming. In this paper, a stochastic gradient-based optimization technique has been used in conjunction with particle filters for object tracking. First, the object that needs to be tracked is detected using the Maximum Average Correlation Height (MACH) filter. The object of interest is detected based on the presence of a correlation peak and average similarity measure. The results of object detection are fed to the tracking routine. The gradient descent technique is employed for object tracking and is used to optimize the particle filters. The gradient descent technique allows particles to converge quickly, allowing less time for the object to be tracked. The results of the proposed algorithm are compared with similar state-of-the-art tracking algorithms on five datasets that include both artificial moving objects and humans to show that the gradient-based tracking algorithm provides better results, both in terms of accuracy and speed.<\/jats:p>","DOI":"10.3390\/s22031098","type":"journal-article","created":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T08:20:29Z","timestamp":1643617229000},"page":"1098","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Tracking of a Fixed-Shape Moving Object Based on the Gradient Descent Method"],"prefix":"10.3390","volume":"22","author":[{"given":"Haris","family":"Masood","sequence":"first","affiliation":[{"name":"Electrical Engineering Department, Wah Engineering College, University of Wah, Wah Cantt 47040, Pakistan"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-0716-3932","authenticated-orcid":false,"given":"Amad","family":"Zafar","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, The Ibadat International University, Islamabad 54590, Pakistan"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-7326-1813","authenticated-orcid":false,"given":"Muhammad Umair","family":"Ali","sequence":"additional","affiliation":[{"name":"Department of Unmanned Vehicle Engineering, Sejong University, Seoul 05006, Korea"}]},{"given":"Tehseen","family":"Hussain","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Wah Engineering College, University of Wah, Wah Cantt 47040, Pakistan"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-6763-2123","authenticated-orcid":false,"given":"Muhammad Attique","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Computer Science, HITEC University Taxila, Taxila 47040, Pakistan"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-7672-1187","authenticated-orcid":false,"given":"Usman","family":"Tariq","sequence":"additional","affiliation":[{"name":"College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-9990-1084","authenticated-orcid":false,"given":"Robertas","family":"Dama\u0161evi\u010dius","sequence":"additional","affiliation":[{"name":"Department of Applied Informatics, Vytautas Magnus University, 44404 Kaunas, Lithuania"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1016\/j.asoc.2018.05.023","article-title":"Soft Computing based object detection and tracking approaches: State-of-the-Art survey","volume":"70","author":"Kaushal","year":"2018","journal-title":"Appl. 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