Your browser doesn't support javascript.
loading
Audio Guide for Visually Impaired People Based on Combination of Stereo Vision and Musical Tones.
Simões, Walter C S S; Silva, Yuri M L R; Pio, José Luiz de S; Jazdi, Nasser; F de Lucena, Vicente.
Afiliação
  • Simões WCSS; ICOMP-Instituto de Computação, UFAM-Federal University of Amazonas, Manaus 69067-005, Brazil.
  • Silva YMLR; UFAM-CETELI, PPGEE, and PPGI, Federal University of Amazonas, Manaus 69067-005, Brazil.
  • Pio JLS; ICOMP-Instituto de Computação, UFAM-Federal University of Amazonas, Manaus 69067-005, Brazil.
  • Jazdi N; Institute of Industrial Automation and Software Systems, University of Stuttgart, 70550 Stuttgart, Germany.
  • F de Lucena V; UFAM-CETELI, PPGEE, and PPGI, Federal University of Amazonas, Manaus 69067-005, Brazil.
Sensors (Basel) ; 20(1)2019 Dec 25.
Article em En | MEDLINE | ID: mdl-31881738
Indoor navigation systems offer many application possibilities for people who need information about the scenery and the possible fixed and mobile obstacles placed along the paths. In these systems, the main factors considered for their construction and evaluation are the level of accuracy and the delivery time of the information. However, it is necessary to notice obstacles placed above the user's waistline to avoid accidents and collisions. In this paper, different methodologies are associated to define a hybrid navigation model called iterative pedestrian dead reckoning (i-PDR). i-PDR combines the PDR algorithm with a Kalman linear filter to correct the location, reducing the system's margin of error iteratively. Obstacle perception was addressed through the use of stereo vision combined with a musical sounding scheme and spoken instructions that covered an angle of 120 degrees in front of the user. The results obtained in the margin of error and the maximum processing time are 0.70 m and 0.09 s, respectively, with obstacles at ground level and suspended with an accuracy equivalent to 90%.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Brasil País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Brasil País de publicação: Suíça