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@InProceedings{TorrećoPimeRoe:1993:ObSuCu,
               author = "Torre{\~a}o, Jos{\'e} Ricardo de Almeida and Pimentel, 
                         Cec{\'{\i}}lio Jos{\'e} Lins and Roe, Edward",
          affiliation = "{Departamento de Inform{\'a}tica da Universidade Federal de 
                         Pernambuco (UFPE)} and {Departamento de Inform{\'a}tica da 
                         Universidade Federal de Pernambuco (UFPE)} and {Departamento de 
                         Inform{\'a}tica da Universidade Federal de Pernambuco (UFPE)}",
                title = "Obtaining surface curvature and depth information with a 
                         disparity-based photometric stereo",
            booktitle = "Anais...",
                 year = "1993",
               editor = "Figueiredo, Luiz Henrique de and Gomes, Jonas de Miranda",
                pages = "239--246",
         organization = "Simp{\'o}sio Brasileiro de Computa{\c{c}}{\~a}o Gr{\'a}fica e 
                         Processamento de Imagens, 6. (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "Disparity-Based Photometric Stereo, computer vision, photometric 
                         images.",
             abstract = "Disparity-Based Photometric Stereo (DBPS) is a recently introduced 
                         Computer Vision process which extracts a disparity field from two 
                         or more photometric stereo images by tracking the displacement of 
                         pixel intensities resulting from the change in the illumination of 
                         the observed scene. Such photometric-disparity field is akin to 
                         the disparity field due to the change of viewing position in 
                         Stereoscopy, and can be obtained through essentially the same 
                         stereo correspondence algorithms. In the present article, we 
                         relate the photometric-disparity field to the curvature of the 
                         imaged surfaces, and also show how it can be used for the 
                         inference of depth through a new version of the Dual Photometric 
                         Stereo process, which employs two cameras and multiple 
                         illuminations. We illustrate our approach with a neural net 
                         simulation of the stereo correspondence algorithms.",
  conference-location = "Recife",
      conference-year = "19 - 22 out. 1993",
                 isbn = "978-85-7669-271-3",
             language = "en",
                  ibi = "8JMKD3MGPBW34M/3D85HNS",
                  url = "http://urlib.net/rep/8JMKD3MGPBW34M/3D85HNS",
           targetfile = "28 Obtaining surface curvature.pdf",
                 type = "Vis{\~a}o por Computador",
               volume = "1",
        urlaccessdate = "2020, May 27"
}


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