Light Fields. Johns Hopkins Department of Computer Science Course : Rendering Techniques, Professor: Jonathan Cohen

Similar documents
More and More on Light Fields. Last Lecture

Jingyi Yu CISC 849. Department of Computer and Information Science

Image or Object? Is this real?

Image-based modeling (IBM) and image-based rendering (IBR)

Image-Based Rendering

The Light Field and Image-Based Rendering

But, vision technology falls short. and so does graphics. Image Based Rendering. Ray. Constant radiance. time is fixed. 3D position 2D direction

Image Based Rendering

Computational Photography

Light Field Techniques for Reflections and Refractions

Image-Based Rendering. Johns Hopkins Department of Computer Science Course : Rendering Techniques, Professor: Jonathan Cohen

Structure from Motion and Multi- view Geometry. Last lecture

Image Base Rendering: An Introduction

Modeling Light. Slides from Alexei A. Efros and others

Modeling Light. Michal Havlik

Light Field Rendering

CS : Assignment 2 Real-Time / Image-Based Rendering

Modeling Light. Michal Havlik : Computational Photography Alexei Efros, CMU, Fall 2011

Real-time Generation and Presentation of View-dependent Binocular Stereo Images Using a Sequence of Omnidirectional Images

Lecture 15: Image-Based Rendering and the Light Field. Kayvon Fatahalian CMU : Graphics and Imaging Architectures (Fall 2011)

A Warping-based Refinement of Lumigraphs

CS 283: Assignment 3 Real-Time / Image-Based Rendering

Modeling Light. Michal Havlik : Computational Photography Alexei Efros, CMU, Fall 2007

Modeling Light. On Simulating the Visual Experience

CSc Topics in Computer Graphics 3D Photography

Image-Based Modeling and Rendering

DD2423 Image Analysis and Computer Vision IMAGE FORMATION. Computational Vision and Active Perception School of Computer Science and Communication

Computational Photography

Reconstruction PSNR [db]

Image-Based Rendering. Johns Hopkins Department of Computer Science Course : Rendering Techniques, Professor: Jonathan Cohen

Image-based Rendering with Controllable Illumination

Lazy decompression of surface light fields for precomputed global illumination

3-D Shape Reconstruction from Light Fields Using Voxel Back-Projection

Efficient Free Form Light Field Rendering

Modeling Light. Michal Havlik

CPSC 4040/6040 Computer Graphics Images. Joshua Levine

High-Quality Interactive Lumigraph Rendering Through Warping

Capturing and View-Dependent Rendering of Billboard Models

Optimizing an Inverse Warper

Compression of Lumigraph with Multiple Reference Frame (MRF) Prediction and Just-in-time Rendering

recording plane (U V) image plane (S T)

Ray Casting on Programmable Graphics Hardware. Martin Kraus PURPL group, Purdue University

Image Based Rendering. D.A. Forsyth, with slides from John Hart

Announcements. Mosaics. How to do it? Image Mosaics

Render-To-Texture Caching. D. Sim Dietrich Jr.

Announcements. Mosaics. Image Mosaics. How to do it? Basic Procedure Take a sequence of images from the same position =

Hybrid Rendering for Collaborative, Immersive Virtual Environments

Forward Image Warping

Mosaics. Today s Readings

Image-Based Modeling and Rendering

Real Time Rendering. CS 563 Advanced Topics in Computer Graphics. Songxiang Gu Jan, 31, 2005

A million pixels, a million polygons. Which is heavier? François X. Sillion. imagis* Grenoble, France

Time Critical Lumigraph Rendering

Light Field Spring

Computer Graphics Shadow Algorithms

Digital Image Representation Image Compression

Forward Image Mapping

IMAGE COMPRESSION. Image Compression. Why? Reducing transportation times Reducing file size. A two way event - compression and decompression

Interactive Vizualisation of Complex Real-World Light Sources

Image-Based Rendering and Modeling. IBR Approaches for View Synthesis

CSE 163: Assignment 3 Final Project

Texture Mapping II. Light maps Environment Maps Projective Textures Bump Maps Displacement Maps Solid Textures Mipmaps Shadows 1. 7.

Image-Based Modeling and Rendering. Image-Based Modeling and Rendering. Final projects IBMR. What we have learnt so far. What IBMR is about

Image-Based Rendering. Image-Based Rendering

Image Warping and Mosacing

Computational Photography

CS4670: Computer Vision

3D Texture Modeling. Polygonal Model. 3D Texture. 3D Texture Cell Selection. Polygonal Model with Selected 3D Texture Cells. 3D Texture Compression

WATERMARKING FOR LIGHT FIELD RENDERING 1

Tour Into the Picture using a Vanishing Line and its Extension to Panoramic Images

IMAGE COMPRESSION. October 7, ICSY Lab, University of Kaiserslautern, Germany

Morphable 3D-Mosaics: a Hybrid Framework for Photorealistic Walkthroughs of Large Natural Environments

Projective Texture Mapping with Full Panorama

International Journal of Advanced Research in Computer Science and Software Engineering

CSL 859: Advanced Computer Graphics. Dept of Computer Sc. & Engg. IIT Delhi

A Review of Image- based Rendering Techniques Nisha 1, Vijaya Goel 2 1 Department of computer science, University of Delhi, Delhi, India

Wireless Communication

Optimization of the number of rays in interpolation for light field based free viewpoint systems

Triangle Rasterization

Image-Based Rendering using Image-Warping Motivation and Background

Chapter 2 - Fundamentals. Comunicação Visual Interactiva

Shear-Warp Volume Rendering. Volume Rendering Overview

Topic 5 Image Compression

Light-Dependent Texture Mapping

Hard Shadows Aliasing and Remedies

CSE528 Computer Graphics: Theory, Algorithms, and Applications

Capturing, Modeling, Rendering 3D Structures

CS602 Midterm Subjective Solved with Reference By WELL WISHER (Aqua Leo)

Morphological: Sub-pixel Morhpological Anti-Aliasing [Jimenez 11] Fast AproXimatte Anti Aliasing [Lottes 09]

3D Rasterization II COS 426

3D Polygon Rendering. Many applications use rendering of 3D polygons with direct illumination

Light Field Rendering using Matrix Optics

QUALITY-BASED IMPROVEMENT OF QUANTIZATION FOR LIGHT FIELD COMPRESSION

Volumetric Scene Reconstruction from Multiple Views

Rate-distortion Optimized Streaming of Compressed Light Fields with Multiple Representations

Volume Rendering. Lecture 21

VIDEO FOR VIRTUAL REALITY LIGHT FIELD BASICS JAMES TOMPKIN

Point-Based Rendering

Polyhedral Visual Hulls for Real-Time Rendering

Rendering. Converting a 3D scene to a 2D image. Camera. Light. Rendering. View Plane

Transcription:

Light Fields Light Fields By Levoy and Hanrahan, SIGGRAPH 96 Representation for sampled plenoptic function stores data about visible light at various positions and directions Created from set of images Resamplings employ data from lots of different images 1

Light Field Dimensionality Position and direction for each sample is a 5D space For empty space (no occlusion), space reduced to 4D sample is constant along a line light field defined on 4D space of directed lines Slab Representation (u,v) Define two parallel planes uv-plane and st-plane (s,t) Light field defined as L(u,v,s,t) (r,g,b) for each (u,v,s,t) tuple Use multiple slabs to cover larger space 2

Sampling Typically create regular sampling of uvand st-planes Place eye point at (u,v) on the uv-plane Generate image with each corresponding to a point on the st-plane each pixel for image (u,v) supplies sample (u,v,x,y) using skewed perspective matrix, (x,y) = (s,t) Data looks like 2D array of 2D images Visualization of Light Field from Levoy and Hanrahan, Light Field Rendering, Proceedings of SIGGRAPH 96, page 34. 3

Generating Samples Using rendered images Place eye at (u,v) Skew projection to cover proper (s,t) range Generate image Using real photographs (looking inward) Computer-controlled camera on planar gantry Camara tilts to center on object (s,t) resampled from (x,y) Object platform (and lighting) rotates to capture different slabs Stanford Light Field Gantry from Levoy and Hanrahan, Light Field Rendering, Proceedings of SIGGRAPH 96, page 36. 4

Resampling Foreach pixel in the rendered image compute line coordinates (intersections with uv- and st-planes Apply nearest neighbor, bilinear, or quadralinear sampling to generate value of pixel from nearby lines in light field Computing Line Parameters Possible using ray/plane intersection Faster using texture mapping to take advantage of plane coherence Store (u,v) coordinates in texture map Render uv-plane as textured rectangle Look up (u,v) coordinates for each pixel Repeat for (s,t) coordinates 5

Anti-aliasing Pre-filter data to remove aliases Integrate over range of eye points to filter (u,v) Apply lens aperture to filter (s,t) Filter size should be consistent with sample spacing Compression Light fields can be BIG (gigabytes) Want to transmit over internet Want to fit in memory Need random access during reconstruction Compression can be slow, decompression must be fast 6

Two Stage Compression/Decompression Lossy vector quantization (VQ) compression Decompose data into small chunks, described as vector Train with data to generate codebook (containing codewords to represent) Store index of best codeword for each vector Lossless entropy coding (using gzip) Decompression Decompress entropy coding (gunzip) on loading to memory entropy coding doesn t allow random access Decompress vector quantization (fast lookup) for each line sample on the fly May compress 24:1 for VQ, 5:1 for gzip, total of 120:1 7

Videos Levoy and Hanrahan. Light Field Rendering. Proceedings of SIGGRAPH 96. Sloan, Cohen, and Gortler. Time Critical Lumigraph Rendering. Proceedings of 1997 Symposium on Interactive 3D Graphics. 8