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Adam Yeh

Adam Yeh. UCF Computer Vision REU Week 1. About Me. Cornell University, Computer Science, c/o 2009 Coursework: Data Structures/Algorithms Functional Programming Java, C, Matlab Computation, Information, and Intelligence (TA also) Math courses too: Discrete Math Number Theory

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Adam Yeh

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  1. Adam Yeh UCF Computer Vision REU Week 1

  2. About Me • Cornell University, Computer Science, c/o 2009 • Coursework: • Data Structures/Algorithms • Functional Programming • Java, C, Matlab • Computation, Information, and Intelligence (TA also) • Math courses too: • Discrete Math • Number Theory • Group Theory • Multivariable/DiffEq/Linear Algebra • Goals: • Grad school-Ph.D? Math/CS • Research career… • This is why I’m here…

  3. This Week • Ran Canny/Sobel C code • Ran FingerFinder code (previous REU’s work) • Started writing Canny code in Matlab • For practice in coding (haven’t done it in awhile) • To understand algorithm better • Currently unfinished (still need double thresholding) • Tried an optimization of Java Canny code • For double thresholding, use BFS to find connected edges instead of repeatedly scanning entire image • Only slightly faster • Algorithmically should be faster, but more overhead • Background Research

  4. 1024*1280 pixel image, Threshold=1, 15% • Canny runs in ~9.7s • Modified Canny runs in ~9.5s • Eventually runs out of memory…

  5. Canny: Changing Sigma • Sigmas of 1, 2, 3 (15%) • More blending means less defined edges aren’t caught

  6. Canny: Changing Threshold % • Threshold determined by percentile (best edges are top 15, 5, and 35%) • Bottom threshold is .35 of top threshold • High threshold means only defined edges caught • Low threshold results in noise

  7. Possible Topics • Initially: lip reading as improvement to speech recognition • Rejected because of emphasis on sound as well • Facial Recognition • Work has been started by Dr. Lobo’s students • Modify finger finder? • Learning algorithms: AdaBoost+Support Vector Machines? • 7 basic expressions: Neutral, anger, disgust, fear, joy, sadness, and surprise

  8. Next Week • Background information: • Current Facial Recognition research? • More machine learning/pattern matching techniques • Modify finger code for specific features • Different parts of face e.g. eyes, nose, mouth • Try OpenCV implementation of Viola/Jones • Find database of test images

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