Examinando por Materia "Computer Vision"

Mostrando 1 - 3 de 3
  • Miniatura
    Ítem
    Edge and corner identification for tracking the line of sight
    (Universidad EAFIT, 2005-12-01) S Orozco, María; Ruiz Salguero, Oscar Eduardo; Jasnoch, Uwe; Universidade de Vigo; EAFIT University; GIStec
  • No hay miniatura disponible
    Ítem
    Feasibility of using Monocular Visual SLAM with ROS for robot navigation in warehouses
    (Universidad EAFIT, 2023) Parada Cuadros, Oswaldo José; Castaño Cano, Davinson; Castaño Cano, Davinson
    In recent years, the use of robots in industrial facilities has become widespread. Particularly, the logistics and inventory management industry has benefited from technological advances, however, the high costs of these technologies prevent many companies from adopting this degree of automation. In this research, we propose the feasibility of using monocular Visual SLAM as an alternative to reduce costs in the localization hardware used for robot navigation in warehouses. For that, we study open source implementations, especially those based on ORB-SLAM2, ROS and Ubuntu. Then, we propose a testing environment compose by a Turtle Bot 2 robot and a location that ensembles some of the characteristics of warehouses. Our analysis shows that it is possible to use monocular Visual SLAM in warehouses, however, we mention some elements in the software and hardware that should be fixed or improved in current implementations in order to robustly and safely operate robots in an indoor storage environment.
  • No hay miniatura disponible
    Ítem
    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.