PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Incorporating geometry information with weak classifiers for improved generic visual categorization
Gabriela Csurka, Jutta Willamowski, Chris Dance and Florent Perronnin
In: Image Analysis and Processing – ICIAP 2005 Lecture Notes in Computer Science , 3617 (3617). (2005) Springer , pp. 612-620. ISBN ISBN: 3-540-28869-4

Abstract

In this paper we improve the performance of a generic visual categorizer based on the ''bag of keypatches'' approach using geometric information. More precisely, we consider a large number of simple geometrical relationships between interest points based on the scale, orientation or closeness. Each relationship leads to a weak classifier. The boosting approach is used to select from this multitude of classifiers (several millions in our case) and to combine them effectively with the original classifier. Results are shown on a new challenging 10 class dataset.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:2250
Deposited By:Gabriela Csurka
Deposited On:11 October 2006