Transcript Document

By Vanessa Newey
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Introduction
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Traditional 3D Modeling and Rendering
Image-Based Modeling, Rendering, and
Lighting
Applications
Available Tools
Summary
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Traditional 3D Modeling and
Rendering
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Traditional 3D Modeling and
Rendering Developments
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Hidden Surface Removal Algorithms
Shading Algorithms
Shadow Calculation
Displaying Curved Surfaces
Ray tracing and Radiosity
Powerful Modeling Tools
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Limitations of Traditional 3D
Modeling and Rendering
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Possible to Visualise Complex 3D Models
in Real Time
BUT…
Creating these 3D models requires
Expertise and Time.
Rendering is Slow
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Motivation for Image-based
Modeling and Rendering
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Demand for more complex, realistic
models
Traditional methods slow and costly
Many virtual objects based on real
objects
Advantageous to model directly from
real objects
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Image-based Modeling and
Rendering
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Create 3D models from one or more
images
Re-render creating new views
Easier to model scenes photorealistically
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Image-based Modeling,
Rendering
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Computer GraphicsComputer Vision
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Image-based Modeling
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Images (photographs, renderings) are
used to determine:
Scene Appearance
Scene Geometry
Lighting
Reflectance Characterisics
Kinematic Properties
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Image-based Rendering
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Appearance in available views is used to
determine appearance in novel views
Not necessary to perform full
illumination computations
Rendering is faster
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Image-based Lighting
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Able to Create a Light-based Model
from the images
For each part of the local scene, we
know its irradiance
Allows us to combine real and synthetic
graphics with consistent illumination,
using images as light sources.
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Example
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Example Video
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Stereo Image Capture Rig
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Applications
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VR worlds and Games
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Construction of virtual scenes
Creating terrain from Air-Photos
Images and Video on the WWW
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Video compression, summarisation,
skimming, indexing and selective retrieval
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Tools
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REALVIZ ImageModeler
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ERDAS IMAGINE OrthoMax
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Automated DEM extraction
ERDAS Stereo Analyst
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http://www.realviz.com/
Provides tools for collection, interpretation and
visualisation of 3D geographic information from
stereo imagery
3Q Qlonerator Series
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http://www.3q.com/offerings_tech.htm
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REALVIZ ImageModeler 1
Start the project
Take from 2 to more photos from your scene or object.
No other information is required
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REALVIZ ImageModeler 2
Calibrate cameras
Add common markers to each photographs
ImageModeler automatically calibrates your cameras
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REALVIZ ImageModeler 3
Create a model
Model your scene or object using standard polygon modeling tools:
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REALVIZ ImageModeler 4
Texture a model
Capture textures per face, or unfolded single textures
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REALVIZ ImageModeler 5
Export a model
Export camera, objects and textures to your favorite 3D application
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ERDAS Stereo Analyst
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Challenges
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Automatic scene segmentation
Complex scenes eg. forests
Non-static scenes
Inaccuracies in source photos
Real imagery/computer vision problems
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Camera pose hard to get
Depth even harder to get
Data Size may be huge
Changes Difficult
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lights, geometry, etc.
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Summary
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Overall… exciting developments and
much more potential for Image-based
modeling, rendering and lighting.
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Sources
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http://i31www.ira.uka.de/~oel/ibmr-focus/
http://www.debevec.org/IBMR99/
http://www.cs.berkeley.edu/~debevec/IBMR
http://research.microsoft.com/~szeliski/IBMR98/web/sld001.htm
http://www.esat.kuleuven.ac.be/~pollefey/
3D modeling from images tutorial
http://www.esat.kuleuven.ac.be/~pollefey/SMILE2/tutorial.html
ERDAS Products
http://www2.erdas.com/supportsite/apps_gallery/flume_bed/flume_bed.htm
http://www2.erdas.com/supportsite/apps_gallery/videography/videography_raw.htm
http://www.erdas.com/software/ProductModules.asp?SubGroupID=513&GroupID=1
REALVIZ ImageModeller
http://www.realviz.com
http://www.realviz.com/products/stepbystep.php?product=im
http://www.debevec.org/Campanile/
http://www.sciencedirect.com/science?_ob=ArticleURL&_aset=A-WA-A-AZ-MsSAYVW-UUA-AUWEYAVWAY-ZWCEYCVAE-AZU&_rdoc=8&_fmt=summary&_udi=B6V08-40J1J3P1&_coverDate=08%2F31%2F2000&_cdi=5640&_orig=search&_st=13&_sort=d&_acct=C000028338&_version=1&_urlVersion=
0&_userid=554534&md5=d41937e1648632dae517f65375553a62
http://www.cs.yorku.ca/~vgrlab/projects/imgrender.html
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