کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6936710 869106 2015 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Vehicle detection grammars with partial occlusion handling for traffic surveillance
ترجمه فارسی عنوان
گرامر تشخیص خودرو با دستکاری جزئی برای نظارت بر ترافیک
کلمات کلیدی
دیدگاه کامپیوتر، مدل گرامر دستکاری مشکوک، تشخیص شیء مبتنی بر قسمت، تشخیص خودرو،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Traffic surveillance is an important topic in intelligent transportation systems (ITS). Robust vehicle detection is one challenging problem for complex traffic surveillance. In this paper, we propose an efficient vehicle detection method by designing vehicle detection grammars and handling partial occlusion. The grammar model is implemented by novel detection grammars, including structure, deformation and pairwise SVM grammars. First, the vehicle is divided into its constitute parts, called semantic parts, which can represent the vehicle effectively. To increase the robustness of part detection, the semantic parts are represented by their detection score maps. The semantic parts are further divided into sub-parts automatically. The two-layer division of the vehicle is modeled into a grammar model. Then, the grammar model is trained by a designed training procedure to get ideal grammar parameters, including appearance models and grammar productions. After that, vehicle detection is executed by a designed detection procedure with respect to the grammar model. Finally, the issue of vehicle occlusion is handled by designing and training specific grammars. The strategy adopted by our method is first to divide the vehicle into the semantic parts and sub-parts, then to train the grammar productions for semantic parts and sub-parts by introducing novel pairwise SVM grammars and finally to detect the vehicle by applying the trained grammars. Experiments in practical urban scenarios are carried out for complex traffic surveillance. It can be shown that our method adapts to partial occlusion and various challenging cases.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Transportation Research Part C: Emerging Technologies - Volume 56, July 2015, Pages 80-93
نویسندگان
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