UW-Madison CS 766 - Image-Based Rendering and Modeling (55 pages)

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Image-Based Rendering and Modeling



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Image-Based Rendering and Modeling

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Pages:
55
School:
University of Wisconsin, Madison
Course:
Cs 766 - Computer Vision
Computer Vision Documents

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Image Based Rendering and Modeling l l l Image based rendering IBR A scene is represented as a collection of images 3D model based rendering MBR A scene is represented by a 3D model plus texture maps Differences u u u u u u Many scene details need not be explicitly modeled in IBR IBR simplifies model acquisition process IBR processing speed independent of scene complexity 3D models MBR are more space efficient than storing many images IBR MBR uses conventional graphics pipeline whereas IBR uses pixel reprojection IBR can sometimes use uncalibrated images MBR cannot IBR Approaches for View Synthesis l Non physically based image mapping u l Geometrically correct pixel reprojection u l Image transfer methods e g in photogrammetry Mosaics u l Image morphing Combine two or more images into a single large image or higher resolution image Interpolation from dense image samples u Direct representation of plenoptic function 1 Image Metamorphosis Morphing l Goal Synthesize a sequence of images that smoothly and realistically transforms objects in source image A into objects in destination image B l Method 1 3D Volume Morphing u u u u u Create 3D model of each object Transform one 3D object into another Render synthesized 3D object Hard expensive to accurately model real 3D objects Expensive to accurately render surfaces such as skin feathers fur 2 Image Morphing l Method 2 Image Cross Dissolving u u Pixel by pixel color interpolation Each pixel p at time t 0 1 is computed by combining a fraction of each pixel s color at the same coordinates in images A and B p 1 t pA t pB pA p pB t u 1 t Easy but looks artificial non physical Image Morphing l Method 3 Mesh based image morphing u u u u G Wolberg Digital Image Warping 1990 Warp between corresponding grid points in source and destination images Interpolate between grid points e g linearly using three closest grid points Fast but hard to control so as to avoid unwanted distortions 3 Image Warping l l Goal Rearrange pixels in an



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