Abstract
Head pose estimation is an important area of investigation for understanding human dynamics. Appearance-based methods are one of the popular solutions to this problem. In this paper we present a novel approach using vector quantization that adds spatial information to the feature set. We compare this with raw, Gabor filtered and Wavelet features using the Carnegie Mellon PIE database. Our approach shows increased performance over the other methods.
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© 2006 Springer-Verlag Berlin Heidelberg
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Lopes, J., Singh, S. (2006). Vector Quantization Segmentation for Head Pose Estimation. In: Corchado, E., Yin, H., Botti, V., Fyfe, C. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2006. IDEAL 2006. Lecture Notes in Computer Science, vol 4224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875581_35
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DOI: https://doi.org/10.1007/11875581_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45485-4
Online ISBN: 978-3-540-45487-8
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