Development of a vision and artificial intelligence algorithm with facial emotion recognition

Santos Gonzales C.E.; Esparza Avila K.L.; Galvez Llumpo M.M.; Horna Chavez O.J. · CISCI - Conferencia Iberoamericana en Sistemas, Cibernetica e Informatica (2024) · DOI: 10.54808/cisci2024.01.264

Resumen

Artificial intelligence is a vital tool in the field of mental health, offering new perspectives to improve quality of life. Therefore, it is proposed to develop a facial emotion recognition algorithm using advanced AI techniques. This initiative addresses the complex interactions between biological, psychological, social and family factors that influence people's mental health. Based on the collection and analysis of data from the Facial Expression Recognition (FER) database, which contains facial images labeled with basic human emotions. Image processing used the open source OpenCV library, which provides tools for image analysis. Additionally, AI algorithms and models are implemented in Python, leveraging libraries such as TensorFlow and scikit-learn. This methodology divides data into training, validation and test sets, as well as extracting features and training AI models, such as convolutional neural networks. The results show the performance of the model in emotion classification, supporting its effectiveness in accurately detecting emotional states from facial expressions. © CISCI - Simposium Iberoamericano en Educacion, Cibernetica e Informatica 2024.

Instituciones: Universidad Privada del Norte