Probabilistic Elastic Part Model: A Pose-Invariant Representation for Real-World Face Verification
IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 918-930, 2018.
Pose variation remains to be a major challenge for real-world face recognition. We approach this problem through a probabilistic elastic part model. We extract local descriptors (e.g., LBP or SIFT) from densely sampled multi-scale image patches. By augmenting each descriptor with its location, a Gaussian mixture model (GMM) is trained to ...More
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