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ON THE UTILITY OF CANONICAL CORRELATION ANALYSIS FOR DOMAIN ADAPTATION IN MULTI-VIEW HEADPOSE ESTIMATION

Anoop, KR and Subramanian, Ramanathan and Vonikakis, Vassilios and Ramakrishnan, KR and Winkler, Stefan (2015) ON THE UTILITY OF CANONICAL CORRELATION ANALYSIS FOR DOMAIN ADAPTATION IN MULTI-VIEW HEADPOSE ESTIMATION. In: IEEE International Conference on Image Processing (ICIP), SEP 27-30, 2015, Quebec City, CANADA, pp. 4708-4712.

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Abstract

The utility of canonical correlation analysis (CCA) for domain adaptation (DA) in the context of multi-view head pose estimation is examined in this work. We consider the three problems studied in 1], where different DA approaches are explored to transfer head pose-related knowledge from an extensively labeled source dataset to a sparsely labeled target set, whose attributes are vastly different from the source. CCA is found to benefit DA for all the three problems, and the use of a covariance profile-based diagonality score (DS) also improves classification performance with respect to a nearest neighbor (NN) classifier.

Item Type: Conference Proceedings
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Additional Information: Copy right of this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Keywords: Canonical Correlation Analysis; Domain Adaptation; Head pose classification; Diagonality score
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 17 May 2016 07:04
Last Modified: 17 May 2016 07:04
URI: http://eprints.iisc.ernet.in/id/eprint/53851

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