中文摘要：

在室内场景分类问题中，由于场景本身结构的复杂性和多样性，存在各种干扰因素，影响分类的准确性．针对上述问题，文中提出基于视觉敏感区域信息增强的室内场景分类算法，通过融合基于视觉敏感区域信息增强的局部特征与全局特征，构成多尺度空间一频率融合特征，实现对室内场景的正确分类．在3个标准测试集上的实验表明，文中算法对多个不同场景分类数据集均有较好的分类结果，适用性较强．

英文摘要：

In the indoor scene classification, the classification accuracy is affected by various interference factors caused by the complexity and diversity of the scene structure itself. Aiming at these problems, an indoor scene classification algorithm based on the information enhancement of visual sensitive area is proposed in this paper. By fusing the local features and the global features based on the visual sensitive region information, the multi-scale space-frequency fusion feature is constructed to classify the indoor scenes correctly. Experimental results on 3 testing sets show that the proposed algorithm obtains good classification results on different scene classification datasets with strong applicability.