Uso de APIs de Computación Afectiva para el análisis de la emoción facial en el aula de clases

Abstract

Abstract: Human beings naturally express information about their emotions and mood through facial expression. This study is an area of fundamental research and remains active since the work "The expression of emotions in man and animals" Darwin C, (1872). This area has presented a great impulse at present thanks to the advance in areas such as Artificial Vision and Machine Learning. The main challenges presented by the development of a functional system lie in the extraction of facial information (characteristics) and interpretation of the human face by the computer, favoring the differentiation of emotions. The present Thesis synthesizes the knowledge and skills acquired during the Computer Systems Engineering Career, about: "Use of Affective Computing APIs for Facial Emotion analysis in the classroom." A system is implemented that performs the automation of validation tasks of the identity of the students and the subsequent detection of emotions within the classroom using a dataSet with information collected from each student.