Emotion Recognition using a Cauchy Naive Bayes Classifier
ثبت نشده
چکیده
Recognizing human facial expression and emotion by computer is an interesting and challenging problem. In this paper we propose a method for recognizing emotions through facial expressions displayed in video sequences. We introduce the Cauchy Naive Bayes classifier which uses the Cauchy distribution as the model distribution and we provide a framework for choosing the best model distribution assumption. Our person-dependent and person-independent experiments show that the Cauchy distribution assumption typically provides better results than the Gaussian distribution assumption.
منابع مشابه
Emotion Recognition Using a Cauchy Naive Bayes Classifier
Recognizing human facial expression and emotion by computer is an interesting and challenging problem. In this paper we propose a method for recognizing emotions through facial expressions displayed in video sequences. We introduce the Cauchy Naive Bayes classifier which uses the Cauchy distribution as the model distribution and we provide a framework for choosing the best model distribution as...
متن کاملA New Approach for Text Documents Classification with Invasive Weed Optimization and Naive Bayes Classifier
With the fast increase of the documents, using Text Document Classification (TDC) methods has become a crucial matter. This paper presented a hybrid model of Invasive Weed Optimization (IWO) and Naive Bayes (NB) classifier (IWO-NB) for Feature Selection (FS) in order to reduce the big size of features space in TDC. TDC includes different actions such as text processing, feature extraction, form...
متن کاملGenetic Algorithm and Neural Network for Face Emotion Recognition
Human being possesses an ability of communication through facial emotions in day to day interactions with others. Some study in perceiving facial emotions has fascinated the human computer interaction environments. In recent years, there has been a growing interest in improving all aspects of interaction between humans and computers especially in the area of human emotion recognition by observi...
متن کاملUsing Multiple Databases for Training in Emotion Recognition: To Unite or to Vote?
We present an extensive study on the performance of data agglomeration and decision-level fusion for robust cross-corpus emotion recognition. We compare joint training with multiple databases and late fusion of classifiers trained on single databases, employing six frequently used corpora of natural or elicited emotion, namely ABC, AVIC, DES, eNTERFACE, SAL, VAM, and three classifiers i. e. SVM...
متن کاملSpeech Emotion Recognition with Emotion-Pair Based Framework Considering Emotion Distribution Information in Dimensional Emotion Space
In this work, an emotion-pair based framework is proposed for speech emotion recognition, which constructs more discriminative feature subspaces for every two different emotions (emotion-pair) to generate more precise emotion bi-classification results. Furthermore, it is found that in the dimensional emotion space, the distances between some of the archetypal emotions are closer than the others...
متن کامل