Kernels on attributed pointsets with applications

Parsana, M and Bhattacharya, S and Bhattacharyya, C and Ramakrishnan, KR (2008) Kernels on attributed pointsets with applications. In: 21st Annual Conference on Neural Information Processing Systems, NIPS 2007, 3 - 6 December 2007.

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Abstract

This paper introduces kernels on attributed pointsets, which are sets of vectors embedded in an euclidean space. The embedding gives the notion of neighborhood, which is used to define positive semidefinite kernels on pointsets. Two novel kernels on neighborhoods are proposed, one evaluating the attribute similarity and the other evaluating shape similarity. Shape similarity function is motivated from spectral graph matching techniques. The kernels are tested on three real life applications: face recognition, photo album tagging, and shot annotation in video sequences, with encouraging results.

Item Type:	Conference Paper
Publication:	Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference
Publisher:	Neural Information Processing Systems
Additional Information:	The copyright for this article belongs to the Neural Information Processing Systems.
Keywords:	Vector spaces, Attribute similarity; Embeddings; Euclidean spaces; Matching techniques; Neighbourhood; Positive semidefinite; Real-life applications; Shape similarity; Similarity functions; Spectral graph matching, Face recognition
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation Division of Electrical Sciences > Electrical Engineering
Date Deposited:	17 Jul 2023 09:55
Last Modified:	17 Jul 2023 09:55
URI:	https://eprints.iisc.ac.in/id/eprint/82437

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