LS-SIFT: Enhancing the Robustness of SIFT During Pose-Invariant Face Recognition by Learning Facial Landmark Specific Mappings
Shinfeng D. Lin,
Paulo E. Linares Otoya
Abstract:The proper functioning of many real-world applications in biometrics and surveillance depends on the robustness of face recognition systems against pose, and illumination variations. In this work, we employ ensemble systems in conjunction with local descriptors to address pose-invariant face recognition (PIFR). Facial landmarks are detected during the first step with a two fold usage. The landmark locations are employed to perform head pose classification (HPC). HPC allows to select only the visible landmarks … Show more
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