{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T13:27:35Z","timestamp":1782394055025,"version":"3.54.5"},"reference-count":36,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,2,29]],"date-time":"2024-02-29T00:00:00Z","timestamp":1709164800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National High Technology Research and Development Program of China","award":["2016YFD0701003"],"award-info":[{"award-number":["2016YFD0701003"]}]},{"name":"National High Technology Research and Development Program of China","award":["SJCX23_1488"],"award-info":[{"award-number":["SJCX23_1488"]}]},{"name":"National High Technology Research and Development Program of China","award":["SJCX23_1499"],"award-info":[{"award-number":["SJCX23_1499"]}]},{"name":"Postgraduate Research &amp; Practice Innovation Program of Jiangsu Province","award":["2016YFD0701003"],"award-info":[{"award-number":["2016YFD0701003"]}]},{"name":"Postgraduate Research &amp; Practice Innovation Program of Jiangsu Province","award":["SJCX23_1488"],"award-info":[{"award-number":["SJCX23_1488"]}]},{"name":"Postgraduate Research &amp; Practice Innovation Program of Jiangsu Province","award":["SJCX23_1499"],"award-info":[{"award-number":["SJCX23_1499"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The lack of discernible vehicle contour features in low-light conditions poses a formidable challenge for nighttime vehicle detection under hardware cost constraints. Addressing this issue, an enhanced histogram of oriented gradients (HOGs) approach is introduced to extract relevant vehicle features. Initially, vehicle lights are extracted using a combination of background illumination removal and a saliency model. Subsequently, these lights are integrated with a template-based approach to delineate regions containing potential vehicles. In the next step, the fusion of superpixel and HOG (S-HOG) features within these regions is performed, and the support vector machine (SVM) is employed for classification. A non-maximum suppression (NMS) method is applied to eliminate overlapping areas, incorporating the fusion of vertical histograms of symmetrical features of oriented gradients (V-HOGs). Finally, the Kalman filter is utilized for tracking candidate vehicles over time. Experimental results demonstrate a significant improvement in the accuracy of vehicle recognition in nighttime scenarios with the proposed method.<\/jats:p>","DOI":"10.3390\/s24051590","type":"journal-article","created":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T03:31:23Z","timestamp":1709263883000},"page":"1590","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Vision-Based On-Road Nighttime Vehicle Detection and Tracking Using Improved HOG Features"],"prefix":"10.3390","volume":"24","author":[{"given":"Li","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China"},{"name":"Changzhou Xingyu Automotive Lighting System Co., Ltd., 182 Qinling Road, Changzhou 213000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiyue","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering & Rail Transit, Changzhou University, Changzhou 213164, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cong","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering & Rail Transit, Changzhou University, Changzhou 213164, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingping","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Shabestari, Z.B., Hosseininaveh, A., and Remondino, F. 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