1 / 11

Image-Based Rendering from a Single Image

Image-Based Rendering from a Single Image. Image-Based Rendering of Diffuse, Specular and Glossy Surface from a Single Image. Inverse Rendering from a Single Image. Samuel Boivin – Andre Gagalowicz. Introduction. To recover an approximation of BRDF of surface from a Single Image

abra-ramirez
Download Presentation

Image-Based Rendering from a Single Image

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Image-Based Rendering from a Single Image Image-Based Rendering of Diffuse, Specular and Glossy Surface from a Single Image. Inverse Rendering from a Single Image Samuel Boivin – Andre Gagalowicz

  2. Introduction To recover an approximation of BRDF of surface from a Single Image ( specular, isotropic, anisotropic surface ) General Principle Hierarchical & Iterative technique Using the error (render image / real image)

  3. Elements of Reflectance Recovery • Input – 3D geometrical model, single image • Object Reflectance : from the Pixel • Problems ( all surfaces reflectance recovery image ) - geometrical model - size of projection

  4. Elements of Reflectance Recovery • Geometrical Model Invisible, Difficult to compute reflectance ( no information ) • Notion of Group of Objects & Surfaces. same reflectance property objects, surfaces – Group • size of projection ( small projection area ) - same reflectance property, bigger projection area – join - better approximation reflectance. - no other bigger object – very rough approximation, biased • Feedback, Comparison ( real image / synthetic image ) - bias is considerably reduced.

  5. Elements of Reflectance Recovery • Reflectance Model and Data Description Image-based Modeling. parameters for complex BRDF – diffuse, specular, isotropic, anisotropic [Ward] Measuring and modeling anisotropic reflection – SIGGRAPH 92 • 3D Geometrical Modeling

  6. Initialization step: All surfaces are perfectly diffuse (radiances average / group) Real Image Diffuse Perfect Specular Non-perfect Specular Isotropic Anisotropic Textured error Image Image difference Reflectance Correction 3D Geometrical Model Rendering Software Synthetic Image inverse rendering process

  7. Inverse Rendering from a Single Image • The case of perfect Diffuse surface Iterative correction of the diffuse reflectance d using this average value • The case of perfectly specular surfaces (s = 1, d = 0) The simplest case because d and s are constant • The case of non-perfectly specular surfaces (s  1, d = 0) Iterative correction of s minimizing the error (real & synthetic image) • The case of both diffuse and specular surfaces (s  0, d  0, no roughness) Minimized error is a function of two parameters

  8. Inverse Rendering from a Single Image • The case of isotropic surfaces (d, s  0, ) d interval [0 1] / s ,  minimization • The case of anisotropic surfaces ( d, s  0, x, y, x ) • The case of textured surfaces Impossible to separate specular reflection and/or shadows from texture itself • Inverse Rendering Method - Single Image, Various type of Reflectance - Textured surface, Particular cases

  9. Original real image without direct estimation of the anisotropic direction without direct estimation of the anisotropic direction with direct estimation of the anisotropic direction with direct estimation of the anisotropic direction

More Related