Geometry-constrained spatial pyramid adaptation for image classification
| Autor: | H. Emrah Tasli, A. Aydin Alatan, Theo Gevers, Ronan Sicre |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Contextual image classification
Segmentation-based object categorization business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-space segmentation Pattern recognition Geometry Image segmentation Pascal (programming language) Image texture Region growing Computer Science::Computer Vision and Pattern Recognition Artificial intelligence Range segmentation business computer Mathematics computer.programming_language |
| Zdroj: | ICIP |
| DOI: | 10.1109/icip.2014.7025209 |
| Popis: | This paper proposes a geometry-constrained spatial pyramid adaptation approach for the image classification task. Scene geometry is used as an input parameter for generating the spatial pyramid definitions. The resulting region adaptation is performed in accordance with the predefined geometric guidelines and underlying image characteristics. Using an approximate global geometric correspondence, exploits the idea that images of the same category share a spatial similarity. This assumption is evaluated and justified in an object classification framework, in which generated region segments are used as an enhancement to the widely utilized “spatial pyramid” method. Fixed region pyramids are replaced by the proposed locally coherent geometrically consistent region segments. Performance of the proposed method on object classification framework is evaluated on the 20 class Pascal VOC 2007 dataset. The proposed method shows consistent increase in the mean average precision (MAP) score for different experimental scenarios. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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