CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
Object Categorization Using Local Feature Context
Tao Sun; Chunjie Zhang; Jing Liu; Hanqing Lu
Conference NameInternational Conference on Advances in Multimedia Modeling
Source PublicationProceedings, Part II. Lecture Notes in Computer Science 7733
Conference DateJanuary 7-9, 2013
Conference PlaceHuangshan, China
AbstractRecently, the use of context has been proven very effective for object categorization. However, most of the researchers only used context information at the visual word level without considering the context information of local features. To tackle this problem, in this paper, we propose a novel object categorization method by considering the local feature context. Given a position in an image, to represent this position’s visual information, we use the local feature on this position as well as other local features based on their distances and angles to this position. The use of local feature context is more discriminative and is also invariant to rotation and scale change. The local feature context can then be combined with the state-of-the-art methods for object categorization. Experimental results on the UIUC-Sports dataset and the Caltech-101 dataset demonstrate the effectiveness of the proposed method.
KeywordBag Of Visual Words Local Feature Context Sift Object Categorization
Document Type会议论文
Corresponding AuthorJing Liu
Recommended Citation
GB/T 7714
Tao Sun,Chunjie Zhang,Jing Liu,et al. Object Categorization Using Local Feature Context[C],2013.
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