This paper presents an approach to face alignment under variable illumination, an obstacle largely ignored in previous 2D alignment work. To account for illumination variation, our method employs two forms of relatively lightinginvariant information. Edge phase congruency is adopted to coarsely localize facial features, since prominent feature edges can be robustly located in the presence of shading and shadows. To accurately deal with features with less pronounced edges, final alignment is

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... computed from intrinsic gray-level information recovered using a proposed form of local intensity normalization. With this approach, our face alignment system works efficiently and effectively under a wide range of illumination conditions, as evidenced by extensive experimentation.