中文摘要：

为了使用国画底层视觉特征对国画作者进行分类预测，提出了利用监督式异构稀疏特征进行选择的方法．首先通过提取多种底层异构视觉特征对国画风格进行描述，建立国画高级语义信息向底层视觉的映射；然后从这些异构特征中选择出最能代表该作者独特风格的特征子集，实现不同画家迥异的绘画风格与国画底层稀疏特征的对应与转换；最后利用这些特征子集对国画作者进行预测，完成分类任务．实验结果表明，该方法具有较好的国画分类性能．

英文摘要：

In order to use low-level visual features of Chinese paintings to predict the author, we present a supervised heterogeneous sparse feature selection method for Chinese paintings classification. Firstly, a variety of low-level heterogeneous visual features are used to describe the painting style of Chinese paintings and mapped to high-level semantic information. Then a subset of features are selected to best represent the author＇s unique style from these heterogeneous features, so as to achieve the correspondence and transformation between the different painting styles of Chinese paintings and the underlying sparse features. Finally, the subset of features are used to forecast Chinese painting author and the classification task. Experimental results show that our method has good classification performance on traditional Chinese paintings.