Improved spatial pyramid matching for image classification

Authors:
Mohammad Shahiduzzaman;Dengsheng Zhang;Guojun Lu
Affiliations:
Gippsland School of IT, Monash University, Australia;Gippsland School of IT, Monash University, Australia;Gippsland School of IT, Monash University, Australia
Venue:
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Year:
2010

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Abstract

Spatial analysis of salient feature points has been shown to be promising in image analysis and classification. In the past, spatial pyramid matching makes use of both of salient feature points and spatial multiresolution blocks to match between images. However, it is shown that different images or blocks can still have similar features using spatial pyramid matching. The analysis and matching will be more accurate in scale space. In this paper, we propose to do spatial pyramid matching in scale space. Specifically, pyramid match histograms are computed in multiple scales to refine the kernel for support vector machine classification. We show that the combination of salient point features, scale space and spatial pyramid matching improves the original spatial pyramid matching significantly.