Abstract
This paper presents a study on the facial feature detection performance achieved using the Viola-Jones framework. A set of classifiers using two different focuses to gather the training samples is created and tested on four different datasets covering a wide range of possibilities. The results achieved should serve researchers to choose the classifier that better fits their demands.
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Castrillón-Santana, M., Hernández-Sosa, D., Lorenzo-Navarro, J. (2011). Viola-Jones Based Detectors: How Much Affects the Training Set?. In: Vitrià, J., Sanches, J.M., Hernández, M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21257-4_37
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DOI: https://doi.org/10.1007/978-3-642-21257-4_37
Publisher Name: Springer, Berlin, Heidelberg
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