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Review Papers | Computer Science & Engineering | India | Volume 4 Issue 6, June 2015
Comparative Study of Face Recognition Algorithm on Cohn-Kanade Database
Radhika Sharma [2] | Abhay Sharma
Abstract: Distinctive machine learning routines are deliberately inspected on a number of databases. After having a lot research in this field, it is examined that LBP features are viable and productive for facial expression recognition. We further developed Boosted-LBP to concentrate the most discriminant LBP feature, and the best recognition performance is achieved by utilizing support Vector Machine classifiers with Boosted-LBP features. Also, we examine LBP features for low-determination facial expression recognition, which is a discriminating issue however occasional tended to in the existing work. We see in our investigations that LBP elements perform steadily and vigorously more than a valuable scope of low resolutions of face pictures, and yield promising outcome in compacted low-resolution video sequence caught in real world environment.
Keywords: Face recognition, dummy face, Cohn-kanade database, Adaboost, biometrics
Edition: Volume 4 Issue 6, June 2015,
Pages: 2653 - 2656