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Proceedings Paper

Robust head pose estimation using locality-constrained sparse coding
Author(s): Hyunduk Kim; Sang-Heon Lee; Myoung-Kyu Sohn
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Paper Abstract

Sparse coding (SC) method has been shown to deliver successful result in a variety of computer vision applications. However, it does not consider the underlying structure of the data in the feature space. On the other hand, locality constrained linear coding (LLC) utilizes locality constraint to project each input data into its local-coordinate system. Based on the recent success of LLC, we propose a novel locality-constrained sparse coding (LSC) method to overcome the limitation of the SC. In experiments, the proposed algorithms were applied to head pose estimation applications. Experimental results demonstrated that the LSC method is better than state-of-the-art methods.

Paper Details

Date Published: 8 December 2015
PDF: 5 pages
Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 98750G (8 December 2015); doi: 10.1117/12.2228507
Show Author Affiliations
Hyunduk Kim, DGIST (Korea, Republic of)
Sang-Heon Lee, DGIST (Korea, Republic of)
Myoung-Kyu Sohn, DGIST (Korea, Republic of)

Published in SPIE Proceedings Vol. 9875:
Eighth International Conference on Machine Vision (ICMV 2015)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev, Editor(s)

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