Ranking Images Based on Aesthetic Qualities
Ranking Images Based on Aesthetic Qualities
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DOI：
10.1109/icpr.2014.587
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发表时间：
2014-08
期刊：
影响因子：
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通讯作者：
A. Gaur;K. Mikolajczyk
中科院分区：
文献类型：
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作者：
A. Gaur;K. Mikolajczyk
我们提出了一种基于视觉美学定性评估的图像表征学习方法。它依赖于表示图像属性及其关系的多节点多状态模型。该模型是从注释者提供的成对图像偏好中学习的。为了证明其有效性，我们将我们的方法应用于时尚形象评分，即对审美品质的比较评估。特征包目标识别用于对图像中的视觉属性进行分类，例如衣服和身体形状。然后为这些属性及其关系分配学习潜力，这些学习潜力用于对图像进行评级。对该表示模型的评价表明，该模型在对时尚图像进行排序时具有较高的性能。
We propose a novel approach for learning image representation based on qualitative assessments of visual aesthetics. It relies on a multi-node multi-state model that represents image attributes and their relations. The model is learnt from pair wise image preferences provided by annotators. To demonstrate the effectiveness we apply our approach to fashion image rating, i.e., comparative assessment of aesthetic qualities. Bag-of-features object recognition is used for the classification of visual attributes such as clothing and body shape in an image. The attributes and their relations are then assigned learnt potentials which are used to rate the images. Evaluation of the representation model has demonstrated a high performance rate in ranking fashion images.