Benchmarking still-to-video face recognition via partial and local linear discriminant analysis on COX-S2V dataset

• Main Authors: HUANG, Zhiwu, SHAN, S., ZHANG, H., LAO, S., KUERBAN, A., CHEN, X.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2012
• Subjects: Face Recognition; Video Sequence; Linear Discriminant Analysis; Face Image; Video Frame; Artificial Intelligence and Robotics; OS and Networks
• Online Access: https://ink.library.smu.edu.sg/sis_research/6543; https://ink.library.smu.edu.sg/context/sis_research/article/7546/viewcontent/Benchmarking_still_to_video_face_recognition.pdf
• Institution: Singapore Management University

In this paper, we explore the real-world Still-to-Video (S2V) face recognition scenario, where only very few (single, in many cases) still images per person are enrolled into the gallery while it is usually possible to capture one or multiple video clips as probe. Typical application of S2V is mug-s...