What parts of a shape are discriminative?

Ramakrishna Kakarala

Ramakrishna Kakarala

(Nanyang Technological University)

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Date: 11/05/2013


What is distinctive about the shape of an apple? The answer likely depends on comparison to similar shapes. The reason to study this question is that shape is a distinguishing feature of objects, and is therefore useful for object recognition in computer vision. Though shape is useful, when objects have similar overall shapes, discriminating among them becomes difficult; successful object recognition calls for the identification of important parts of the shapes. In this talk we introduce the concept of discriminative parts and propose a method to identify them. We show how we can assign levels of importance to different regions of contours, based on their discriminative potential. Our experiments show that the method is promising and can identify semantically meaningful segments as being important ones. We place our work in context by reviewing the related work on saliency.

Further Information:

Ramakrishna Kakarala is an Associate Professor in the School of Computer Engineering at the Nanyang Technological University (NTU) in Singapore. He has worked in both academia and industry; prior to joining NTU, he spent 8 years at Agilent Laboratories in Palo Alto, and at Avago Technologies in San Jose. He received the Ph.D. in Mathematics at UC Irvine, after completing a B.Sc. in Computer Engineering at the University of Michigan. Two of his students have recently won awards: the BAE Systems award at EI 2012, and the Best Student Paper award at ICIP 2013. The latter award went to Vittal Premachandran, whose Ph.D. thesis work at NTU is the basis of this talk.

Created: Tuesday, November 5th, 2013