Performance Improvement for Classifiers by Optimizing Training Samples

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A precise vehicle detection-and-tracking algorithm that is robust for the appearance change of the objects has been determined using an optimization of the training sample-set.An algorithm for obtaining the Random-Subset SVM ensemble is determined. The algorithm combines some weak-classifiers that are trained by small samples extracted from whole training sample set. The required training time for the ensemble classifier is considered to be smaller than the training a classifier using full-set of training samples, while attaining better generalization performance.