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Carnegie Mellon Robotics Institute

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Abstract

Abstract Sparsely registering a face (i.e., locating 2 fiducial points) is considered a much easier task than densely registering one; especially with varying viewpoints. Unfortunately, the converse tends to be true for the task of viewpoint-invariant face verification; the more registration points one has the better the performance. In this paper we present a novel approach to viewpoint invariant face verification which we refer to as the "patch-whole" algorithm. The algorithm is able to obtain good verification performance with sparsely registered faces. Good performance is achieved by not assuming any alignment between gallery and probe view faces, but instead trying to learn the joint likelihood functions for faces of similar and dissimilar identities. Generalization is encouraged by factorizing the joint gallery and probe appearance likelihood, for each class, into an ensemble of "patch-whole" likelihoods. We make an additional contribution in this paper by reviewing existing approaches to viewpoint-invariant face verification and demonstrating how most of them fall into one of two categories; namely viewpoint-generative or viewpoint-discriminative. This categorization is instructive as it enables us to compare our "patch-whole" algorithm to other paradigms in viewpoint-invariant face verification and also gives deeper insights into why the algorithm performs so well.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Associated Lab(s) / Group(s): Human Identification at a Distance and Face Group

Associated Project(s): Face Recognition Across Pose

Number of pages: 14

Text Reference

Simon Lucey and Tsuhan Chen, "A Viewpoint Invariant, Sparsely Registered, Patch Based, Face Verifier," International Journal of Computer Vision (IJCV), , December, 2007

BibTeX Reference

@article{Lucey_2007_6031,
   author = "Simon Lucey and Tsuhan Chen",
   title = "A Viewpoint Invariant, Sparsely Registered, Patch Based, Face Verifier",
   journal = "International Journal of Computer Vision (IJCV)",
   month = "December",
   year = "2007",
}

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