Computational Photography Light Field Rendering Jinxiang Chai

Image-based Modeling: Challenging Scenes Why will they produce poor results? - lack of discernible features - occlusions - difficult to capture high-level structure - illumination changes - specular surfaces

Some Solutions - Use priors to constrain the modeling space - Aid modeling process with minimal user interaction - Combine image-based modeling with other modeling approaches

Videos Morphable face (click here)here Image-based tree modeling (click here)here Video trace (click here)here 3D modeling by ortho-images (Click here)here

Spectrum of IBMR Images user input range scans Model Images Image based modeling Image- based rendering Geometry+ Images Light field Images + Depth Geometry+ Materials Panoroma Kinematics Dynamics Etc. Camera + geometry

Outline Light field rendering [Levoy and Hanranhan SIG96] 3D light field (concentric mosaics) [Shum and He Sig99]

Plenoptic Function Can reconstruct every possible view, at every moment, from every position, at every wavelength Contains every photograph, every movie, everything that anyone has ever seen! it completely captures our visual reality! An image is a 2D sample of plenoptic function! P(x,y,z,θ,φ,λ,t)

Ray Let’s not worry about time and color: 5D 3D position 2D direction P(x,y,z,  )

Static objectCamera No Change in Radiance Static Lighting How can we use this?

Static objectCamera No Change in Radiance Static Lighting How can we use this?

Ray Reuse Infinite line Assume light is constant (vacuum) 4D 2D direction 2D position non-dispersive medium Slide by Rick Szeliski and Michael Cohen

Only need plenoptic surface

Synthesizing novel views Assume we capture every ray in 3D space!

Synthesizing novel views

Light field / Lumigraph Outside convex space 4D Stuff Empty

Light Field How to represent rays? How to capture rays? How to use captured rays for rendering

Light Field How to represent rays? How to capture rays? How to use captured rays for rendering

Light field - Organization 2D position 2D direction s 

Light field - Organization 2D position 2 plane parameterization s u

Light field - Organization 2D position 2 plane parameterization u s t s,t u,v v s,t u,v

Light field - Organization Hold u,v constant Let s,t vary What do we get? s,tu,v

Lumigraph - Organization Hold s,t constant Let u,v vary An image s,tu,v

Lightfield / Lumigraph

Light field/lumigraph - Capture Idea 1 Move camera carefully over u,v plane Gantry >see Light field paper s,tu,v

Stanford multi-camera array 640 × 480 pixels × 30 fps × 128 cameras synchronized timing continuous streaming flexible arrangement

q For each output pixel determine s,t,u,v either use closest discrete RGB interpolate near values s u Light field/lumigraph - rendering

Nearest closest s closest u draw it Blend 16 nearest quadrilinear interpolation s u

Ray interpolation s u Nearest neighbor Linear interpolation in S-T Quadrilinear interpolation

Image Plane Camera Plane Light Field Capture Rendering Light Field/Lumigraph Rendering

Light fields Advantages: No geometry needed Simpler computation vs. traditional CG Cost independent of scene complexity Cost independent of material properties and other optical effects Disadvantages: Static geometry Fixed lighting High storage cost

3D plenoptic function Image is 2D Light field/lumigraph is 4D What happens to 3D? - 3D light field subset - Concentric mosaic [Shum and He]

3D light field One row of s,t plane i.e., hold t constant s,t u,v

3D light field One row of s,t plane i.e., hold t constant thus s,u,v a “row of images” s u,v

Concentric mosaics [Shum and He] Polar coordinate system: - hold r constant - thus (θ,u,v)

Concentric mosaics Why concentric mosaic? - easy to capture - relatively small in storage size

Concentric mosaics From above How to captured images?

Concentric mosaics From above How to render a new image?

Concentric mosaics From above How to render a new image? - for each ray, retrieval the closest captured rays

Concentric mosaics From above How to render a new image? - for each ray, retrieval the closest captured rays

Concentric mosaics From above How to render a new image? - for each ray, retrieval the closest captured rays

Concentric mosaics From above object How to retrieval the closest rays?

Concentric mosaics From above object (s,t) interpolation plane How to retrieve the closest rays?

Concentric mosaics From above object (s,t) interpolation plane How to retrieve the closest rays?

Concentric mosaics From above object (s,t) interpolation plane How to retrieve the closest rays?

Concentric mosaics From above object (s,t) interpolation plane How to retrieve the closest rays?

Concentric mosaics From above object (s,t) interpolation plane How to synthesize the color of rays?

Concentric mosaics From above object (s,t) interpolation plane How to synthesize the color of rays? - bilinear interpolation

Concentric mosaics From above

Concentric mosaics From above

Concentric mosaics What are limitations?

Concentric mosaics What are limitations? - limited rendering region? - large vertical distortion