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    • 10. 发明授权
    • Studying aesthetics in photographic images using a computational approach
    • 使用计算方法学习摄影图像中的美学
    • US08755596B2
    • 2014-06-17
    • US13542326
    • 2012-07-05
    • Ritendra DattaJia LiJames Z. Wang
    • Ritendra DattaJia LiJames Z. Wang
    • G06K9/62
    • G06K9/6228G06K9/00624G06K9/4652G06K9/4671
    • 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.
    • 使用例如同行评级的在线照片共享网站作为数据源,使用视觉内容作为机器学习问题自动推断图片的美学品质。 基于它们可以在美学上令人不愉快的图像之间区分的直觉来提取图像的某些视觉特征。 一维支持向量机用于识别与基于社区的美学评级具有显着相关性的特征。 使用支持向量机和分类树构建自动分类器,并采用简单的特征选择启发式来消除不相关的特征。 特征的多项式项的线性回归也用于推断数字美学评级。