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Author Choudhury, Tanzeem ♦ Clarkson, Brian ♦ Jebara, Tony ♦ Pentland, Alex
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Pose Variation ♦ Natural Real-time Input ♦ Person Identification Technique ♦ Audio Clip ♦ Reliable Videoframe ♦ Multimodal Person Recognition ♦ Unconstrained Video ♦ Verification Rate ♦ Human Head ♦ Auditory Background ♦ Depth Information ♦ Frontal Face Image ♦ Registered Client ♦ Recognition Algorithm ♦ Clean Speech
Description We propose a person identification technique that can recognize and verify people from unconstrained video and audio. We do not expect fully frontal face image or clean speech as our input. Our recognition algorithm can detect and compensate for pose variation and changes in the auditory background and also select the most reliable videoframe and audio clip to use for recognition. We also use 3D depth information of a human head to detect the presenceofanactualperson as opposed to an image of that person. Our system achieves 100% recognition and verification rates on natural real-time input with 26 registered clients.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 1998-01-01