Sketch-based warping of RGBN images

نویسندگان

  • Thiago Pereira
  • Emilio Vital Brazil
  • Ives Macedo
  • Mario Costa Sousa
  • Luiz Henrique de Figueiredo
  • Luiz Velho
چکیده

1524-0703/$ see front matter 2010 Elsevier Inc doi:10.1016/j.gmod.2010.11.001 ⇑ Corresponding author. Fax: +55 21 25295067. E-mail addresses: [email protected] (T. Pereira), Brazil), [email protected] (I. Macêdo), smcosta@ucalg [email protected] (L.H. de Figueiredo), [email protected] (L While current image deformation methods are careful in making the new geometry seem right, little attention has been given to the photometric aspects. We introduce a deformation method that results in coherently illuminated objects. For this task, we use RGBN images to support a relighting step integrated in a sketch-based deformation method. We warp not only colors but also normals. Normal warping requires smooth warping fields. We use sketches to specify sparse warping samples and impose additional constraints for region of interest control. To satisfy these new constraints, we present a novel image warping method based on Hermite–Birkhoff interpolation with radial basis functions that results in a smooth warping field. We also use sketches to help the system identify both lighting conditions and material from single images. We present results with RGBN images from different sources, including photometric stereo, synthetic images, and photographs. 2010 Elsevier Inc. All rights reserved.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Normal Synthesis on Rgbn Images

In this work, we synthesize normals and color to add geometric details to an RGBN image (image with a color and a normal channel). Existing modeling and image processing tools are not apt to edit RGBN images directly. Since high resolution RGBN images can be obtained using photometric stereo, we used them as full models and as exemplars in a Texture from Example synthesis. Our method works on R...

متن کامل

Normal Synthesis on RGBN Images

In this work, we synthesize normals and color to add geometric details to an RGBN image (image with a color and a normal channel). Existing modeling and image processing tools are not apt to edit RGBN images directly. Since high resolution RGBN images can be obtained using photometric stereo, we used them as full models and as exemplars in a Texture from Example synthesis. Our method works on R...

متن کامل

NormalShop: Modeling surface mesostructure

Normals 1 have been used in geometry acquisition and rendering for years. However, modeling with normals is limited because of the lack of formally defined operations. We present surface normal operations built on two key ingredients. First, a separation of models in two levels, while the base surface is represented by positions in a mesh, the details are only represented through normals in a p...

متن کامل

A Nonlinear Grayscale Morphological and Unsupervised method for Human Facial Synthesis Based on an Example Image

Human facial generation of example image is used as a requirement for biometric applications for the purpose of identifying individuals. In this paper, face generation consists of three main steps. In the first step, detection of significant lines and edges of the example image are carried out using nonlinear grayscale morphology. Then, hair areas are identified from the face of sample. The fin...

متن کامل

Retrieval of Hand-Sketched Envelopes in Logo Images

This paper introduces an approach for retrieving envelope of high-level object groupings in bi-level images with multiple objects. Motivated by studies in Gestalt theory, hierarchical clustering is used to detect the envelope and group its objects based on their spatial proximity, area, shape features and orientation. To decide the final grouping, the grouping outcomes are combined using an evi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Graphical Models

دوره 73  شماره 

صفحات  -

تاریخ انتشار 2011