Robust real-time face tracker for cluttered environments

摘要

A multi-stage system for single face tracking in cluttered scenes is presented. Initial candidate face locations are identified using a modified version of the ratio template algorithm [Proceedings of the Fifteenth National Conference on Artificial Intelligence (1998)]. This operates by matching ratios of averaged luminance using a spatial face model adapted here to incorporate biological proportions (the golden ratio). We find the inclusion in the face template of these golden ratio proportions increases tolerance to illumination changes. Subsequent processing stages enable rejection of false positives. These stages include a novel ratio-ratios operator that improves recognition rates by examining higher order relationships within the initial ratio template measures, and simple morphological eye and mouth feature detection. This frontal-face tracking architecture runs in real-time and is applicable to problem domains where face localisation is required.