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Authors: Andreas Savakis and James Schimmel

Affiliation: Rochester Institute of Technology, United States

Keyword(s): Pose estimation, image retrieval, neural networks, eye detector, mouth detector.

Abstract: Face detection is a prominent semantic feature which, along with low-level features, is often used for content-based image retrieval. In this paper we present a human facial pose estimation method that can be used to generate additional metadata for more effective image retrieval when a face is already detected. Our computationally efficient pose estimation approach is based on a simplified geometric head model and combines artificial neural network (ANN) detectors with template matching. Testing at various poses demonstrated that the proposed method achieves pose estimation within 4.28 degrees on average, when the facial features are accurately detected.

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Paper citation in several formats:
Savakis, A. and Schimmel, J. (2007). FACIAL POSE ESTIMATION FOR IMAGE RETRIEVAL. In Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP; ISBN 978-972-8865-74-0; ISSN 2184-4321, SciTePress, pages 173-177. DOI: 10.5220/0002061201730177

@conference{visapp07,
author={Andreas Savakis. and James Schimmel.},
title={FACIAL POSE ESTIMATION FOR IMAGE RETRIEVAL},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP},
year={2007},
pages={173-177},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002061201730177},
isbn={978-972-8865-74-0},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP
TI - FACIAL POSE ESTIMATION FOR IMAGE RETRIEVAL
SN - 978-972-8865-74-0
IS - 2184-4321
AU - Savakis, A.
AU - Schimmel, J.
PY - 2007
SP - 173
EP - 177
DO - 10.5220/0002061201730177
PB - SciTePress

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