In this paper, we experimentally study the combination of face and facial feature detectors to improve face detection performance. The face detection problem, as suggeted by recent face detection challenges, is still not solved. Face detectors traditionally fail in large-scale problems and/or when the face is occluded or different head rotations are present. The combination of face and facial feature detectors is evaluated with a public database. The obtained results evidence an improvement in the positive detection rate while reducing the false detection rate. Additionally, we prove that the integration of facial feature detectors provides useful information for pose estimation and face alignment. © 2012 Springer-Verlag.
CITATION STYLE
Castrillón-Santana, M., Hernández-Sosa, D., & Lorenzo-Navarro, J. (2012). Combining face and facial feature detectors for face detection performance improvement. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7441 LNCS, pp. 82–89). https://doi.org/10.1007/978-3-642-33275-3_10
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