Abstract：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.
史静，朱虹，王婧，薛杉. 基于视觉敏感区域信息增强的室内场景分类算法*[J]. 模式识别与人工智能, 2017, 30(6): 520-529.
SHI Jing, ZHU Hong, WANG Jing, XUE Shan. Indoor Scene Classification Algorithm Based on Information Enhancement of Vision Sensitive Area. , 2017, 30(6): 520-529.
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