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face-2010 - Computer Vision Mubarak Shah Computer Vision...

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Unformatted text preview: Computer Vision Mubarak Shah Computer Vision Lab University of Central Florida Orlando, FL 32816 Computer Vision • The ability of computers to see. – Image Understanding – Machine Vision – Robot Vision – Image Analysis – Video Understanding A picture is worth a thousand words. A word is worth a thousand pictures. A HUNT Image • 2-D array of numbers (intensity values, gray levels) • Gray levels 0 (black) to 255 (white) • Color image is 3 2-D arrays of numbers – Red – Green – Blue • Resolution (number of rows and columns) – 128X128 – 256X256 – 512X512 – 640X480 Image Formats • TIF • PGM • PBM • GIF • JPEG Video • Sequence of frames • 30 frames per second • Formats – AVI – MPEG – Quick Time Video Clip Sequence of Images Digitization • TV camera is analog, need – A to D converter – Frame grabber • Digital Cameras do not need digitization – JVC (MPEG through fire wire, USB) – Sony (MPEG through fire wire, USB) –--- Face Recognition Simple Approach • Recognize faces (mug shots) using gray levels (appearance) • Each image is mapped to a long vector of gray levels • Several views of each person are collected in the model-base during training • During recognition a vector corresponding to an...
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