کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6938046 1449921 2018 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Photographic composition classification and dominant geometric element detection for outdoor scenes
ترجمه فارسی عنوان
طبقه بندی عکاسی و تشخیص عناصر هندسی غالب برای صحنه های در فضای باز
کلمات کلیدی
طبقه بندی عکس، ترکیب عکاسی، تشخیص عنصر ترکیب تشخیص عنصر هندسی، تشخیص آسمان، حکم سوم،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Despite the practical importance of photographic composition for improving or assessing the aesthetical quality of photographs, only a few simple composition rules have been considered for its classification. In this work, we propose novel techniques to classify photographic composition rules of outdoor scenes and detect dominant geometric elements, called composition elements, for each composition class. Specifically, we first categorize composition rules of outdoor photographs into nine classes: RoT, center, horizontal, symmetric, diagonal, curved, vertical, triangle, and pattern. Then, we develop a photographic composition classification algorithm using a convolutional neural network (CNN). To train the CNN, we construct a photographic composition database, which is publicly available. Finally, for each composition class, we propose an effective scheme to locate composition elements, i.e., bounding boxes for main subjects, leading lines, axes of symmetry, triangles, and sky regions. Extensive experimental results demonstrate that the proposed algorithm classifies composition classes reliably and detects composition elements accurately.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 55, August 2018, Pages 91-105
نویسندگان
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