@InProceedings{Mena-ChalcoMacêVelhCesa:2008:PC3DFa,
               author = "Mena-Chalco, Jes{\'u}s P. and Mac{\^e}do, Ives and Velho, Luiz 
                         Carlos Pacheco Rodrigues and Cesar-Jr, Roberto M.",
          affiliation = "{IME - Universidade de Sao Paulo} and {Instituto Nacional de 
                         Matem{\'a}tica Pura e Aplicada} and {Instituto Nacional de 
                         Matem{\'a}tica Pura e Aplicada} and {IME - Universidade de Sao 
                         Paulo}",
                title = "PCA-based 3D Face Photography",
            booktitle = "Proceedings...",
                 year = "2008",
               editor = "Jung, Cl{\'a}udio Rosito and Walter, Marcelo",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 21. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "3D photography, principal component analysis, computer vision.",
             abstract = "This paper presents a 3D face photography system based on a small 
                         set of training facial range images. The training set is composed 
                         by 2D texture and 3D range images (i.e. geometry) of a single 
                         subject with different facial expressions. The basic idea behind 
                         the method is to create texture and geometry spaces based on the 
                         training set and transformations to go from one space to the 
                         other. The main goal of the proposed approach is to obtain a 
                         geometry representation of a given face provided as a texture 
                         image, which undergoes a series of transformations through the 
                         texture and geometry spaces. Facial feature points are obtained by 
                         an active shape model (ASM) extracted from the 2D gray-level 
                         images. PCA then is used to represent the face dataset, thus 
                         defining an orthonormal basis of texture and range data. An input 
                         face is given by a gray-level face image to which the ASM is 
                         matched. The extracted ASM is fed to the PCA basis representation 
                         and a 3D version of the 2D input image is built. The experimental 
                         results on static images and video sequences using seven samples 
                         as training dataset show rapid reconstructed 3D faces which 
                         maintain spatial coherence similar to the human perception, thus 
                         corroborating the efficiency of our approach.",
  conference-location = "Campo Grande, MS, Brazil",
      conference-year = "12-15 Oct. 2008",
                  doi = "10.1109/SIBGRAPI.2008.40",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2008.40",
             language = "en",
                  ibi = "6qtX3pFwXQZG2LgkFdY/UNsdi",
                  url = "http://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/UNsdi",
           targetfile = "MenaChalco-3DFacePhotography.pdf",
        urlaccessdate = "2024, Apr. 28"
}