Abstract
Most face detection methods require high or medium resolution face images to attain satisfactory results. However, in many surveillance applications, where there is a need to image wide fields of view, faces cover just a few pixels, which makes their detection difficult. Despite its importance, little work has been aimed at providing reliable detection at these low resolutions. In this work, we study the relationship between resolution and the automatic face detection rate with the Modified Census Transform, one of the most successful algorithms for face detection presented to date, and propose a new Color Census Transform that provides significantly better results than the original when applied to low-resolution color images.
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Zheng, J., Ramírez, G.A., Fuentes, O. (2010). Face Detection in Low-Resolution Color Images. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2010. Lecture Notes in Computer Science, vol 6111. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13772-3_46
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DOI: https://doi.org/10.1007/978-3-642-13772-3_46
Publisher Name: Springer, Berlin, Heidelberg
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