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Head Pose Detection Based on Fusion of Multiple Viewpoint Information

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4122))

Abstract

This paper presents a novel approach to the problem of determining head pose estimation and face 3D orientation of several people in low resolution sequences from multiple calibrated cameras. Spatial redundancy is exploited and the head in the scene is detected and geometrically approximated by an ellipsoid. Skin patches from each detected head are located in each camera view. Data fusion is performed by back-projecting skin patches from single images onto the estimated 3D head model, thus providing a synthetic reconstruction of the head appearance. Finally, these data are processed in a pattern analysis framework thus giving an estimation of face orientation. Tracking over time is performed by Kalman filtering. Results of the proposed algorithm are provided in the SmartRoom scenario of the CLEAR Evaluation.

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References

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Rainer Stiefelhagen John Garofolo

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© 2007 Springer Berlin Heidelberg

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Canton-Ferrer, C., Casas, J.R., Pardàs, M. (2007). Head Pose Detection Based on Fusion of Multiple Viewpoint Information. In: Stiefelhagen, R., Garofolo, J. (eds) Multimodal Technologies for Perception of Humans. CLEAR 2006. Lecture Notes in Computer Science, vol 4122. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69568-4_28

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  • DOI: https://doi.org/10.1007/978-3-540-69568-4_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69567-7

  • Online ISBN: 978-3-540-69568-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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