Expression Recognition with Ri-HOG Cascade
نویسندگان
چکیده
This paper presents a novel classification framework derived from AdaBoost to classify facial expressions. The proposed framework adopts rotation-reversal invariant HOG as features. The Framework is implemented through configuring the Area under ROC curve (AUC) of the weak classifier with HOG, which is a discriminative classification framework. The proposed classification framework is evaluated with two very popular and representative public databases: MMI and AFEW. As a result, it outperforms the state-of-the-arts methods. This paper presents a novel classification framework derived from AdaBoost to classify facial expressions. The proposed framework adopts rotation-reversal invariant HOG as features. The Framework is implemented through configuring the Area under ROC curve (AUC) of the weak classifier with HOG, which is a discriminative classification framework. The proposed classification framework is evaluated with two very popular and representative public databases: MMI and AFEW. As a result, it outperforms the state-ofthe-arts methods.
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