Robust face alignment under occlusion via regional predictive power estimation
Face alignment has been well studied in recent years, however, when a face alignment model is applied on facial images with heavy partial occlusion, the performance deteriorates significantly. In this paper, instead of training an occlusion-aware model with visibility annotation, we address this issue via a model adaptation scheme that uses the result of a local regression forest (RF) voting method. In the proposed scheme, the consistency of the votes of the local RF in each of several...[Show more]
|Collections||ANU Research Publications|
|Source:||IEEE Transactions on Image Processing|
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