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LEARNING GEOMETRY-FREE FACE RE-LIGHTING
Title
LEARNING GEOMETRY-FREE FACE RE-LIGHTING.
Creator
Moore, Thomas, Foroosh, Hassan, University of Central Florida
Abstract / Description
The accurate modeling of the variability of illumination in a class of images is a fundamental problem that occurs in many areas of computer vision and graphics. For instance, in computer vision there is the problem of facial recognition. Simply, one would hope to be able to identify a known face under any illumination. On the other hand, in graphics one could imagine a system that, given an image, the illumination model could be identified and then used to create new images. In this thesis...
Show moreThe accurate modeling of the variability of illumination in a class of images is a fundamental problem that occurs in many areas of computer vision and graphics. For instance, in computer vision there is the problem of facial recognition. Simply, one would hope to be able to identify a known face under any illumination. On the other hand, in graphics one could imagine a system that, given an image, the illumination model could be identified and then used to create new images. In this thesis we describe a method for learning the illumination model for a class of images. Once the model is learnt it is then used to render new images of the same class under the new illumination. Results are shown for both synthetic and real images. The key contribution of this work is that images of known objects can be re-illuminated using small patches of image data and relatively simple kernel regression models. Additionally, our approach does not require any knowledge of the geometry of the class of objects under consideration making it relatively straightforward to implement. As part of this work we will examine existing geometric and image-based re-lighting techniques; give a detailed description of our geometry-free face re-lighting process; present non-linear regression and basis selection with respect to image synthesis; discuss system limitations; and look at possible extensions and future work.
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Date Issued
2007
Identifier
CFE0001893, ucf:47394
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001893
IMAGE-BASED MATERIAL EDITING
Title
IMAGE-BASED MATERIAL EDITING.
Creator
Khan, Erum, Reinhard, Erik, University of Central Florida
Abstract / Description
Photo editing software allows digital images to be blurred, warped or re-colored at the touch of a button. However, it is not currently possible to change the material appearance of an object except by painstakingly painting over the appropriate pixels. Here we present a set of methods for automatically replacing one material with another, completely different material, starting with only a single high dynamic range image, and an alpha matte specifying the object. Our approach exploits the...
Show morePhoto editing software allows digital images to be blurred, warped or re-colored at the touch of a button. However, it is not currently possible to change the material appearance of an object except by painstakingly painting over the appropriate pixels. Here we present a set of methods for automatically replacing one material with another, completely different material, starting with only a single high dynamic range image, and an alpha matte specifying the object. Our approach exploits the fact that human vision is surprisingly tolerant of certain (sometimes enormous) physical inaccuracies. Thus, it may be possible to produce a visually compelling illusion of material transformations, without fully reconstructing the lighting or geometry. We employ a range of algorithms depending on the target material. First, an approximate depth map is derived from the image intensities using bilateral filters. The resulting surface normals are then used to map data onto the surface of the object to specify its material appearance. To create transparent or translucent materials, the mapped data are derived from the object's background. To create textured materials, the mapped data are a texture map. The surface normals can also be used to apply arbitrary bidirectional reflectance distribution functions to the surface, allowing us to simulate a wide range of materials. To facilitate the process of material editing, we generate the HDR image with a novel algorithm, that is robust against noise in individual exposures. This ensures that any noise, which would possibly have affected the shape recovery of the objects adversely, will be removed. We also present an algorithm to automatically generate alpha mattes. This algorithm requires as input two images--one where the object is in focus, and one where the background is in focus--and then automatically produces an approximate matte, indicating which pixels belong to the object. The result is then improved by a second algorithm to generate an accurate alpha matte, which can be given as input to our material editing techniques.
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Date Issued
2006
Identifier
CFE0001462, ucf:47065
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001462