PAL lab meeting 25, May, 2006 (Casey): Fast Rotation Invariant Multi-View Face Detection Based on Real Adaboost

Title: Fast Rotation Invariant Multi-View Face Detection Based on Real Adaboost

Authors: Bo WU, Haizhou AI, Chang HUANG and Shihong LAO
(Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China)
(Sensing Technology Laboratory, Omron Corporation)

AbstractIn this paper, we propose a rotation invariant multiviewface detection method based on Real Adaboostalgorithm [1]. Human faces are divided into severalcategories according to the variant appearance fromdifferent view points. For each view category, weakclassifiers are configured as confidence-rated look-uptable(LUT) of Haar feature [2]. Real Adaboostalgorithm is used to boost these weak classifiers andconstruct a nesting-structured face detector. To make itrotation invariant, we divide the whole 360-degree rangeinto 12 sub-ranges and construct their correspondingview based detectors separately. To improve performance,a pose estimation method is introduced and results in aprocessing speed of four frames per second on 320 ×240sized image. Experiments on faces with 360-degree inplanerotation and ±90-degree out-of-plane rotation arereported, of which the frontal face detector subsystemretrieves 94.5% of the faces with 57 false alarms on theCMU+MIT frontal face test set and the multi-view facedetector subsystem retrieves 89.8% of the faces with 221false alarms on the CMU profile face test set.