Coupling alignments with recognition for still-to-video face recognition

• Main Authors: HUANG, Zhiwu, ZHAO, X., SHAN, S., WANG, R., CHEN, X.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: coupling alignments with recognition; still-to-video face recognition; Artificial Intelligence and Robotics; OS and Networks
• Online Access: https://ink.library.smu.edu.sg/sis_research/6545; https://ink.library.smu.edu.sg/context/sis_research/article/7548/viewcontent/Coupling_alignments_with_recognition_for_still_to_video_face_recognition.pdf
• Institution: Singapore Management University

The Still-to-Video (S2V) face recognition systems typically need to match faces in low-quality videos captured under unconstrained conditions against high quality still face images, which is very challenging because of noise, image blur, low face resolutions, varying head pose, complex lighting, and...