PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Spatial Weighting for Bag-of-Features
Marcin Marszalek and Cordelia Schmid
In: CVPR 2006(2006).


This paper presents an extension to category classification with bag-of-features, which represents an image as an orderless distribution of features. We propose a method to exploit spatial relations between features by utilizing object boundaries provided during supervised training. We boost the weights of features that agree on the position and shape of the object and suppress the weights of background features, hence the name of our method - "spatial weighting". The proposed representation is thus richer and more robust to background clutter. Experimental results show that our approach improves the results of one of the best current image classification techniques. Furthermore, we propose to apply the spatial model to object localization. Initial results are promising.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:2306
Deposited By:Marcin Marszalek
Deposited On:16 November 2006