Abstract
In this work we present the preliminary results of a face detection system based on an hybrid approach: it combines typical feature-based techniques with image-based analysis, in order to better exploit the main characteristics available in the input image. Different modules contribute to the face detection task: 1) a template-based approach initially proposed in [12], 2) an edge-extraction technique well suited to deal with illumination-changes, 3) a multiple-classifier specifically designed to discard false positives and 4) a novel method based on a featureless representation of the eye-patterns that further improves the face/non-face discrimination. The experimental results show that the system can localize faces in images with complex background, even in presence of strong illumination changes.
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Nanni, L., Franco, A., Cappelli, R. (2004). Towards a Robust Face Detector. In: Maltoni, D., Jain, A.K. (eds) Biometric Authentication. BioAW 2004. Lecture Notes in Computer Science, vol 3087. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25976-3_6
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DOI: https://doi.org/10.1007/978-3-540-25976-3_6
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