The main objective of this research is to develop a system that recognizes customers’ satisfaction or dissatisfaction in a restaurant based on their facial expressions when receiving the service provided by the establishment. The implementation of the system has a series of stages common to the development of a visual computing project, which will begin with data preprocessing to train the classifier to be used in this case: a support vector machine. This data preprocessing uses the histogram of oriented gradients for detecting a face inside an image, so that only the face outline is cut. In this way, facial landmarks of the image are extracted, the probability that each of the basic feelings appears in the facial expression of people is established, and, based on these probabilities, customers’ satisfaction or dissatisfaction is determined. The results show that the system correctly...

The main objective of this research is to develop a system that recognizes customers’ satisfaction or dissatisfaction in a restaurant based on their facial expressions when receiving the service provided by the establishment. The implementation of the system has a series of stages common to the development of a visual computing project, which will begin with data preprocessing to train the classifier to be used in this case: a support vector machine. This data preprocessing uses the histogram of oriented gradients for detecting a face inside an image, so that only the face outline is cut. In this way, facial landmarks of the image are extracted, the probability that each of the basic feelings appears in the facial expression of people is established, and, based on these probabilities, customers’ satisfaction or dissatisfaction is determined. The results show that the system correctly...

La presente investigación tiene como principal objetivo el desarrollo de un sistema que reconozca la satisfacción o insatisfacción de un cliente en un restaurante con base en los gestos que este mismo realiza al momento de recibir el servicio brindado por el establecimiento. La implementación del sistema cuenta con una serie de etapas comunes al desarrollo de un proyecto de computación visual, las cuales inician con un preprocesamiento de los datos a ser empleados para el entrenamiento del clasificador que se utilizará, en este caso, una máquina de soporte vectorial. Dentro de este preprocesamiento se hace uso del histograma de gradientes, orientados a la detección del rostro dentro de la imagen, para que esta sea recortada solo al contorno de la cara. De esta manera, se continúa con la extracción de los hitos faciales de la imagen, luego se determina la probabilidad de como ca...

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