Facial features detection robust to pose, illumination and identity

This work addresses the problem of automatic detection of salient facial features. Face images are described using local normalized Gaussian receptive fields. Face features are learned using a clustering of the Gaussian derivative responses. We have found that a single cluster provides a robust detector for salient facial features robust to pose, illumination and identity. We describe how this cluster is learned and which facial features have found to be salient.