PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Mining Exemplars for Object Modelling Using Affinity Propagation
Shengping xia and Edwin Hancock
In: S+SSPR 2010, 18-20 Aug 2010, Cesme, Turkey.

Abstract

This paper focusses on the problem of locating object class exemplars from a large corpus of images using anity propagation. We use attributed relational graphs to represent groups of local invariant features together with their spatial arrangement. Rather than mining exemplars from the entire graph corpus, we prefer to cluster object specific exemplars. Firstly, we obtain an object specific cluster of graphs using similarity propagation. The popular anity propagation method is then individually applied to each object specific cluster. Using this clustering method, we can obtain object specific exemplars together with a high precision for the data associated with each exemplar. Experiments are performed on over 80K images spanning ~500 objects, and demonstrate the performance of the method in terms of eciency, scalability.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Machine Vision
Learning/Statistics & Optimisation
ID Code:7357
Deposited By:Edwin Hancock
Deposited On:17 March 2011