关键词: 场景识别, 超像素空间金字塔模型, 空间PACT, bag of words特征, 支持向量机

Abstract: In order to overcome drawbacks of SPM based scene recognition, a novel scene recognition method based on Super-pixel Spatial Pyramid Model（S-SPM） is proposed：images are hierarchically divided into sub-regions through super-
pixel segmentation and then the visual vocabulary is constructed by clustering the Principal component Analysis of Census Transform（PACT） features which are extracted from every corresponding spatial sub-region. To recognize the category of a scene, PACT of all spatial sub-regions are concatenated to form a feature vector and then the bag of words feature are added. Finally the LIBSVM is used to classify the scene category. The experimental results indicate that this method has higher recognition rate.

Key words: scene recognition, S-SPM（Super-pixel Spatial Pyramid Model）, PACT（Principal component Analysis of Census Transform）, bag of words, SVM（Support Vector Machine）