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Enhanced spatial pyramid matching using log-polar-based image subdivision and representation

Abstract
This paper presents a new model for capturing spatial information for object categorization with bag-of-words (BOW). BOW models have recently become popular for the task of object recognition, owing to their good performance and simplicity. Much work has been proposed over the years to improve the BOW model, where the Spatial Pyramid Matching (SPM) technique is the most notable. We propose a new method to exploit spatial relationships between image features, based on binned log-polar grids. Our model works by partitioning the image into grids of different scales and orientations and computing histogram of local features within each grid. Experimental results show that our approach improves the results on three diverse datasets over the SPM technique.
Type
Conference Contribution
Type of thesis
Series
Citation
Zhang, E. & Mayo, M. (2010). Enhanced spatial pyramid matching using log-polar-based image subdivision and representation. Paper accepted for presentation at the International Conference on Digital Image Computing: Techniques and Applications (DICTA), Sydney, Australia, 1–3 December 2010.
Date
2010
Publisher
IEEE
Degree
Supervisors
Rights
This is the author’s accepted version. ©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.