A Parallel Implementation of Error Correction SVM with Applications to Face Recognition
The Error Correction SVM method is an excellent multiclass classification approach and has been applied to face recognition successfully. Yet, it suffers from the computational complexity. To reduce the computation time of the algorithm, a parallel implementation scheme is presented in the paper in which the training and classification tasks are assigned to multiple processors and run on all the processors simultaneously. The simulation experiments conducted on a local area network using Cambridge ORL face database show that the parallel algorithm given in the paper is effective in speeding up the algorithms of the training and classification while maintaining the recognition accuracy unchanged.
KeywordsFace recognition Parallel algorithm Error Correction SVM
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- 2.Asanovic, K., Bodik, R., et al.: The Landscape of Parallel Computing Research: A View from Berkly. Technical report, University of California, Berkeley (2006)Google Scholar
- 5.Kreβel, U.: Pairwise Classification and Support Vector Machines. In: Schölkopr, B., Burges, J.C., Smola, A.J. (eds.) Advances in Kernel Methods: Support Vector Learning. MIT Press, Cambridge (1999)Google Scholar