Robust recognition of facial expressions on noise degraded facial images
Munaf Sheikh · University of the Western Cape Electronic Theses and Dissertations Repository (University of the Western Cape) · 2011
We investigate the use of noise degraded facial images in the application of facial expression recognition.In particular, we trained Gabor+SVM classifiers to recognize facial expressions images with various types of noise.We applied Gaussian noise, Poisson noise, varying levels of salt and pepper noise, and speckle noise to noiseless facial images.Classifiers were trained with images without noise and then tested on the images with noise.Next, the classifiers were trained using images with noise, and then on tested both images that had noise, and images that were noiseless.Finally, classifiers were tested on images while increasing the levels of salt and pepper in the test set.Our results reflected distinct degradation of recognition accuracy.We also discovered that certain types of noise, particularly Gaussian and Poisson noise, boost recognition rates to levels greater than would be achieved by normal, noiseless images.We attribute this effect to the Gaussian envelope component of Gabor filters being sympathetic to Gaussian-like noise, which is similar in variance to that of the Gabor filters.Finally, using linear regression, we mapped a mathematical model to this degradation and used it to suggest how recognition rates would degrade further should more noise be added to the images. February 25, 2011Conducting this research at the University of the Western Cape (UWC) has been a challenging but highly rewarding experience.Over the duration of this research, the following people stand topmost on the list of people who have instrumental in the completion of this endeavour.It is a pleasure to thank those who made this thesis possible: James Connan -Rhodes University, South Africa -is a lecturer of Computer Science, and my supervisor for this thesis.James has gone out of his way to assist in both a professional and personal capacity.Over the period that I've known him, his support and friendship has been invaluable, and I have grown both professionally and as an individual as a result of his guidance.