Examinando por Autor "Gomez, Alejandro"

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    Ítem
    An approach to emotion Recongnition in Single-channel EEG Singgnals using Stationar Wavelet Tansform
    (Springer, 2016-10-26) Gomez, Alejandro; Lucia Quintero M, O.; lopez, Natalia; Castro, Jaime; Mejia, Gonzalo
    The Regional Council of Biomedical Engineering for Latin America (CORAL) will host the VII Latin-American Congress of Biomedical Engineering (CLAIB 2016), October 26 – 28, 2016 at the Universidad Autónoma de Bucaramanga, Colombia. Special events of the co
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    Ítem
    A Novel emotion recognition technique from voiced-speech
    (IEEE, 2017-01-01) Uribe, Alejandro; Gomez, Alejandro; Bastidas, Manuela; Quintero, O. Lucia; Campo, Damian; Uribe, Alejandro; Gomez, Alejandro; Bastidas, Manuela; Quintero, O. Lucia; Campo, Damian; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
    In the framework of the beginning of the investigation due to a work of an undergraduate student, the authors at Mathematical Modeling Research Group (GRIMMAT) propose the use of emotion recognition algorithms previously developed by them adapting it to the FAU Aibo emotion corpus which was the database used in the INTERSPEECH 2009 Emotion Challenge. Firstly, by resampling the audio signal and windowing process, the audio signal is segmented. Next, each segment is decomposed through the discrete wavelet transform, then the descriptive characteristics of the decomposed signal are extracted. Finally, a supervised classification scheme is used. This paper presents the main results and conclusions obtained.
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    Short Research Advanced Project: Development of Strategies for Automatic Facial Feature Extraction and Emotion Recognition
    (IEEE, 2017-10-18) Restrepo, David; Gomez, Alejandro; Restrepo, David; Gomez, Alejandro; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
    Emotions are a fundamental part of the personal and social skills of the human being. The behavior, intelligence, reason and decision making process are some of the topic that can be influenced by the emotional state of a person. In this paper we develop a computational way for emotion recognition though images using the Cohn-Kanade database to train a pattern recognition neural network and Viola Jones object detector to extract the information of the facial expression. The resulting neural network showed an overall accuracy of 90.7% in recognizing between 6 basic emotions such a surprise, fear, happiness, sadness, disgust and anger.