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Preprocessing Images for Facial Recognition

Preprocessing Images for Facial Recognition. Adam Schreiner ECE533. Solution. Problem. Face recognition systems have problems recognizing differences in lighting, pose, facial expressions, and picture quality.

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Preprocessing Images for Facial Recognition

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  1. Preprocessing Images for Facial Recognition Adam Schreiner ECE533

  2. Solution Problem • Face recognition systems have problems recognizing differences in lighting, pose, facial expressions, and picture quality. • Apply some sort of processing to images before they are analyzed to increase success

  3. Process • Create a training set • Read in images • Apply Preprocessing technique • Make it easier to process the data and increase the chances of getting correct matches • Better chances of success with changes in illumination, pose, picture quality. • Decrease processing time. • Format data, calculate the face space • Apply same Preprocessing technique to test images • Run test images against the face space • Rank techniques based on number of correct matches, number of false matches, and time to calculate data

  4. Methods to Test • Smoothing • Blurring • Sharpen • Edge Detection • Image Size • Combinations

  5. Calculating Eigenfaces • Read in Training Set • Apply Processing Technique • Calculate the mean image • Find the difference between each image and the mean image • Calculate L matrix and eigen vectors • Calculate eigenfaces • Keep the M’ images that correspond to highest eigen values as the face space

  6. Verifying Faces • Form a set of weights from training data • Get new face image, apply preprocessing technique • From set of weights for new image • Find the distance between the new face and the training data • If distance is less than a set threshold the face is categorized as the kth person in the database.

  7. Example Eigenfaces

  8. Results • Will be ranked on best performance based upon • Correct matching • Speed • Incorrect matches

  9. References • M. Turk, A. Pentland, Eigenfaces for Recognition, Journal of Cognitive Neurosicence, Vol. 3, No. 1, 1991, pp. 71-86 • W. Zhao, R. Chellappa, A. Rosenfeld, P.J. Phillips, Face Recognition: A Literature Survey, ACM Computing Surveys, 2003, pp. 399-458 • Wikipedia • http://ai.ucsd.edu/Tutorial/matlab.html • ECE533 Course Notes • ECE738 Course Notes

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