Depending on the overall reject rate, our system could get a significant increase in the complete recognition time while the returned accuracy of our system is promising compared to that of the single SVM classifier.
in other experiments using less training data as presented in table 4, we trained the SVM classifier based on the combination of DiffPosNeg and BoW features.