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@InProceedings{MarroquimPfeiCarvOliv:2011:Te3DMo,
               author = "Marroquim, Ricardo and Pfeiffer, Gustavo and Carvalho, Felipe 
                         Moura de and Oliveira, Antonio Alberto Fernades de",
          affiliation = "UFRJ and UFRJ and UFRJ and UFRJ",
                title = "Texturing 3D models with low geometric features",
            booktitle = "Proceedings...",
                 year = "2011",
               editor = "Lewiner, Thomas and Torres, Ricardo",
         organization = "Conference on Graphics, Patterns and Images, 24. (SIBGRAPI)",
            publisher = "IEEE Computer Society Conference Publishing Services",
              address = "Los Alamitos",
             keywords = "3D virtual replica, high-resolution texture mapping, least-squares 
                         minimization.",
             abstract = "This paper presents a texture projection and alignment method 
                         specifically tailored for objects with low geometric features. A 
                         common way to build virtual replicas is to acquire the geometry 
                         with a 3D scanner and model its reflectance properties (i.e. 
                         colors) by projecting photos onto the 3D surface. To correctly 
                         align each photo it is necessary to retrieve the camera's 
                         extrinsic matrix, which is usually achieved by optimization 
                         algorithms that match geometric features of the model with their 
                         corresponding ones on the photos. However, when dealing with 
                         cultural heritage artifacts or mechanical pieces, for example, 
                         some models inherently lack significant geometric detail. We 
                         propose a method to automatically extract these features from high 
                         resolution photos and register them in a sequential manner using a 
                         variation of the contour-based approaches. The algorithm requires 
                         minimum user intervention as only an initial guess of the camera's 
                         direction is required for each photo. In addition, we describe an 
                         improved formulation of the optimization method based on a smooth 
                         function that avoids typical local minima found in this scenario. 
                         The results are illustrated with high-resolution textured models 
                         produced by our system.",
  conference-location = "Macei{\'o}",
      conference-year = "Aug. 28 - 31, 2011",
             language = "en",
           targetfile = "texture-alignment.pdf",
        urlaccessdate = "2019, Dec. 09"
}


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