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Estimating Point of Regard with a Consumer Camera at a Distance

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Pattern Recognition and Image Analysis (IbPRIA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7887))

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Abstract

In this work, we have studied the viability of a novel technique to estimate the POR that only requires video feed from a consumer camera. The system can work under uncontrolled light conditions and does not require any complex hardware setup. To that end we propose a system that uses PCA feature extraction from the eyes region followed by non-linear regression. We evaluated three state of the art non-linear regression algorithms. In the study, we also compared the performance using a high quality webcam versus a Kinect sensor. We found, that despite the relatively low quality of the Kinect images it achieves similar performance compared to the high quality camera. These results show that the proposed approach could be extended to estimate POR in a completely non-intrusive way.

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© 2013 Springer-Verlag Berlin Heidelberg

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Mansanet, J., Albiol, A., Paredes, R., Mossi, J.M., Albiol, A. (2013). Estimating Point of Regard with a Consumer Camera at a Distance. In: Sanches, J.M., Micó, L., Cardoso, J.S. (eds) Pattern Recognition and Image Analysis. IbPRIA 2013. Lecture Notes in Computer Science, vol 7887. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38628-2_104

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  • DOI: https://doi.org/10.1007/978-3-642-38628-2_104

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38627-5

  • Online ISBN: 978-3-642-38628-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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