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espanolEn las ultimas decadas, la cantidad de accidentes de transito debido a la fatiga o somnolencia del conductor ha provocado cuantiosas perdidas humanas y materiales. A su vez, la venta en el parque automotor se ha masificado lo cual indica que posiblemente en los siguientes anos si no se toma las medidas pertinentes para detectar la fatiga existira un incremento en los accidentes automovilisticos. Este trabajo de investigacion propone el desarrollo de un sistema de deteccion de fatiga en los conductores que permita alertar sobre sobre su estado mientras este conduciendo mediante el uso de tecnicas de vision artificial y machine learning. Las tecnicas de estos dos campos de estudio se interceptan para generar modelos supervisados con un alto rendimiento al momento de clasificar el estado de fatiga en los conductores. En este estudio se ha trabajado con un dataset de imagenes frontales enfocandonos en la caracteristica fisiologica de los ojos obteniendo resultados preliminares prometedores en la deteccion de fatiga en tiempo real. EnglishIn recent decades, the number of traffic accidents due to fatigue or drowsiness of the driver has caused significant human and material losses. At the same time, the sale in the vehicle fleet has been massified, which indicates thatpossibly in the following years, if the pertinent measures are not taken to detect fatigue, there will be an increase in automobile accidents. Therefore, in this research study, the development of a fatigue detection system in drivers that allows alerting about their status while driving using artificial vision and machine learning techniques is proposed. The techniques of these two fields of study are intercepted to generate supervised models with high performance when classifying the state of fatigue in drivers. In this study, a dataset of frontal images focusing on the physiological characteristics of the eyes was used; obtaining promising preliminary results in the detection of fatigue in real-time.

Detección del estado fisiológico de los ojos en Conductores mediante técnicas de visión artificial