Fast face recognition using a combination of image pyramid and hierarchical clustering algorithms

Hajar Momeni, Mohammad Taghi Sadeghi, Hamid Reza Abutalebi · 2009

Classifying an unknown object in image retrieval systems using the nearest neighbour classifier would be very time consuming when the number of the objects within the associated database is high. Generating a dendrogram using a Hierarchical Agglomerative Clustering (HAC) algorithm and searching the database images from coarse to fine resolutions using image pyramids are two important groups of techniques widely used for dealing with this problem. In this paper, a novel algorithm is proposed by combining these methods within the framework of a face recognition system. The search process is performed in a coarse-to-fine manner using image pyramids. On the bottom level of the pyramid (the finest resolution), a set of dendrograms is formed using the HAC algorithm. Our experimental studies show that the recognition process can be speeded up by a factor of around 65 compare to the basic nearest neighbour classifier. In such a condition, however, the recognition rate is slightly reduced.

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