author = "Cordeiro, Natal Henrique and Pedrino, Emerson Carlos",
          affiliation = "{Federal Institute of S{\~a}o Paulo and Federal University of 
                         S{\~a}o Carlos} and {Federal University of S{\~a}o Carlos}",
                title = "An Architecture for Collision Risk Prediction for Visually 
                         Impaired People",
            booktitle = "Proceedings...",
                 year = "2018",
               editor = "Ross, Arun and Gastal, Eduardo S. L. and Jorge, Joaquim A. and 
                         Queiroz, Ricardo L. de and Minetto, Rodrigo and Sarkar, Sudeep and 
                         Papa, Jo{\~a}o Paulo and Oliveira, Manuel M. and Arbel{\'a}ez, 
                         Pablo and Mery, Domingo and Oliveira, Maria Cristina Ferreira de 
                         and Spina, Thiago Vallin and Mendes, Caroline Mazetto and Costa, 
                         Henrique S{\'e}rgio Gutierrez and Mejail, Marta Estela and Geus, 
                         Klaus de and Scheer, Sergio",
         organization = "Conference on Graphics, Patterns and Images, 31. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Visually impaired people, prediction, collision risk, dynamic 
             abstract = "The production of sensory substitution equipment for the visually 
                         impaired (VIP) is growing. The aim of this project is to 
                         understand the VIP context and predict the risks of collision for 
                         the VIP, following an analysis of the position, distance, size and 
                         motion of the objects present in their environment. This 
                         understanding is refined by data fusion steps applied to the 
                         Situation Awareness model to predict possible impacts in the near 
                         future. With this goal, a new architecture was designed, composed 
                         of systems that detect free passages, static objects, dynamic 
                         objects and the paths of these dynamic objects. The detected data 
                         was mapped into a 3D plane verifying positions and sizes. For the 
                         fusion, a method was developed that compared four more general 
                         classifiers in order to verify which presented greater reliability 
                         in the given context. These classifiers allowed inferences to be 
                         made when analyzing the risks of collision in different 
                         directions. The architecture designed for risk prediction is the 
                         main contribution of this project.",
  conference-location = "Foz do Igua{\c{c}}u, PR, Brazil",
      conference-year = "Oct. 29 - Nov. 1, 2018",
             language = "en",
           targetfile = "37.pdf",
        urlaccessdate = "2020, Dec. 02"