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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"><head> <link rel="icon" type="image/ico" href="https://it-in-industry.com/index_files/icon.gif"/> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <title>Contour-based Pedestrian Detection with Foreground Distribution Trend Filtering and Tracking | Ng | INFORMATION TECHNOLOGY IN INDUSTRY</title> <meta name="description" content="Contour-based Pedestrian Detection with Foreground Distribution Trend Filtering and Tracking"> <meta name="keywords" content="pedestrian detection; sparse contour; foreground distribution trend; crowded scene"> <meta name="DC.Contributor.Sponsor" xml:lang="en" content=""> <meta name="DC.Creator.PersonalName" content="Kiat Siong Ng"> <meta name="DC.Creator.PersonalName" content="Min-Chun Hu"> <meta name="DC.Creator.PersonalName" content="Yu-Jung Hsiao"> <meta name="DC.Creator.PersonalName" content="Kuang-Yu Nien"> <meta name="DC.Creator.PersonalName" content="Pei-Yin Chen"> <meta name="DC.Date.created" scheme="ISO8601" content="2015-09-14"> <meta name="DC.Date.dateSubmitted" scheme="ISO8601" content="2015-09-14"> <meta name="DC.Date.issued" scheme="ISO8601" content="2015-09-14"> <meta name="DC.Date.modified" scheme="ISO8601" content="2015-09-14"> <meta name="DC.Description" xml:lang="en" content="In this work, we propose a real-time pedestrian detection method for crowded environments based on contour and motion information. Sparse contour templates of human shapes are first generated on the basis of a point distribution model (PDM), then a template matching step is applied to detect humans. To reduce the detecting time complexity and improve the detection accuracy, we propose to take the ratio and distribution trend of foreground pixels inside each detecting window into consideration. A tracking method is further applied to deal with the short-term occlusions and false alarms. The experimental results show that our method can efficiently detect pedestrians in videos of crowded scenes."> <meta name="DC.Format" scheme="IMT" content="application/pdf"> <meta name="DC.Identifier.pageNumber" content="33-37"> <meta name="DC.Identifier.URI" content="http://it-in-industry.com/issue/archive/41.html"> <meta name="DC.Language" scheme="ISO639-1" content="en"> <meta name="DC.Rights" content=" Authors who publish with this journal agree to the following terms: Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. 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content="Kiat Siong Ng"> <meta name="citation_author_institution" content="Department of Computer Science and Information Engineering National Cheng Kung University"> <meta name="citation_author" content="Min-Chun Hu"> <meta name="citation_author_institution" content="Department of Computer Science and Information Engineering National Cheng Kung University"> <meta name="citation_author" content="Yu-Jung Hsiao"> <meta name="citation_author_institution" content="Department of Computer Science and Information Engineering National Cheng Kung University"> <meta name="citation_author" content=" Kuang-Yu Nien"> <meta name="citation_author_institution" content="Department of Computer Science and Information Engineering National Cheng Kung University"> <meta name="citation_author" content="Pei-Yin Chen"> <meta name="citation_author_institution" content="Department of Computer Science and Information Engineering National Cheng Kung University"> <meta name="citation_title" content="Contour-based 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