In this paper, we present a scale independent automatic face location technique which can detect the locations of frontal
human faces from images. Our hierarchical approach of knowledge-based face detection composed of three levels. Level
1 consists of a simple but effective eyes model that generates a set of rules to judge whether or not there exists a human
face candidate in the current search area in a scale-independent manner and in a single scan of the image. To utilize this
model, we define a new operator - extended projection and define two new concepts: single projection line and pair
projection line. At level 2, an improved model of Yang's mosaic image model is applied to check the consistency of
visual features with respect to the human face within each 3x3 blocks of a candidate face image. At the third level, we
apply a SVM based face model, to eliminate the false positives obtained from level 2. Experimental results show the
combined rule-based and statistical approach works well in detecting frontal human faces in uncluttered scenes.
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