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STUDYING AESTHETICS IN PHOTOGRAPHIC IMAGES USING A COMPUTATIONAL APPROACH

机译:使用计算方法研究摄影图像中的美学

摘要

The aesthetic quality of a picture is automatically inferred using visual content as a machine learning problem using, for example, a peer-rated, on-line photo sharing Website as data source. Certain visual features of images are extracted based on the intuition that they can discriminate between aesthetically pleasing and displeasing images. A one-dimensional support vector machine is used to identify features that have noticeable correlation with the community-based aesthetics ratings. Automated classifiers are constructed using the support vector machines and classification trees, with a simple feature selection heuristic being applied to eliminate irrelevant features. Linear regression on polynomial terms of the features is also applied to infer numerical aesthetics ratings.
机译:使用视觉内容作为机器学习问题,例如使用同行评等的在线照片共享网站作为数据源,可以自动推断出图片的美学质量。基于直觉可以提取图像的某些视觉特征,这些直觉可以区分美学上令人愉悦的图像和令人讨厌的图像。一维支持向量机用于识别与基于社区的美学等级具有显着相关性的特征。使用支持向量机和分类树构造自动分类器,并应用简单的特征选择试探法来消除不相关的特征。对特征的多项式项的线性回归也可用于推断数值美学评级。

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