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

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