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.

Date Published: 27 February 2007
PDF: 11 pages
Proc. SPIE 6496, Real-Time Image Processing 2007, 64960P (27 February 2007); doi: 10.1117/12.704657

Published in SPIE Proceedings Vol. 6496:
Real-Time Image Processing 2007
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)