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https://doi.org/10.1109/ICIP.2012.6467251
Title: | Hierarchical object groups for scene classification | Authors: | Sadovnik A. Chen T. |
Keywords: | Image Classification Object Detection Object Groups Scene Classification |
Issue Date: | 2012 | Citation: | Sadovnik A., Chen T. (2012). Hierarchical object groups for scene classification. Proceedings - International Conference on Image Processing, ICIP : 1881-1884. ScholarBank@NUS Repository. https://doi.org/10.1109/ICIP.2012.6467251 | Abstract: | The hierarchical structures that exist in natural scenes have been utilized for many tasks in computer vision. The basic idea is that instead of using strictly low level features it is possible to combine them into higher level hierarchical structures. These higher level structures provide a more specific feature and can thus lead to better results in classification or detection. Although most previous work has focused on hierarchical combinations of low level features, hierarchical structures exist on higher levels as well. In this work we attempt to automatically discover these higher level structures by finding meaningful object groups using the Minimum Description Length (MDL) principle. We then use these structures for scene classification and show that we can achieve a higher accuracy rate using them. | Source Title: | Proceedings - International Conference on Image Processing, ICIP | URI: | http://scholarbank.nus.edu.sg/handle/10635/146117 | ISBN: | 9781467325332 | ISSN: | 15224880 | DOI: | 10.1109/ICIP.2012.6467251 |
Appears in Collections: | Staff Publications |
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