Download Datasets and Benchmarks for Densely Sampled 4D Light Fields

Datasets and Benchmarks for Densely Sampled 4D Light Fields
Sven Wanner, Stephan Meister and Bastian Goldluecke
Heidelberg Collaboratory for Image Processing, University of Heidelberg
e-mail:
http://lightfield-analysis.net
{sven.wanner,stephan.meister,bastian.goldluecke}@iwr.uni-heidelberg.de
Selected light fields in the database
Contributions
Code and benchmarks
Light field datasets
thirteen high quality densely sampled light fields
seven CG generated datasets with ground truth disparity
four of these with ground truth segmentation
six real world datasets captured using a gantry
one transparency dataset with ground truth disparity for both
the surface as well as an object behind it
Suitable for the evaluation of continuous methods for
light field analysis based on epipolar plane images
X
Computer graphics generated with ground truth depth:
CUDA library with complete source code for
continuous optimization and light field analysis
Several methods for disparity reconstruction
Inverse problems: denoising, inpainting,
super-resolution, segmentation
Fully scripted evaluation on the light field
database
Front-end to interface with other databases
4D Light Field Parametrization and Epipolar Plane Images (EPIs)
Light field structure: Lumigraph [2]
Computer graphics generated with ground truth depth and object labels:
Disparity and epipolar plane images
Ω
P = (X, Y, Z)
y
Π
x1
t
x2
∆s
Epipolar plane image [1]
f
s1
x2 − x1 =
s2
Light field parametrization
f
∆s
Z
Disparity equals local slope
Comparison to existing light field data sets
Existing data sets either lack ground truth data for depth and segmentation,
or are sparsely sampled and unsuitable for benchmarking continuous methods.
Stanford Light Field Archive:
More than 20 light fields sampled using a camera array, a gantry and a light field microscope
No ground truth disparities
UCSD/MERL Light Field Repository:
Video and static light fields
No ground truth disparities, one-dimensional domain of view points only
Recorded with the gantry, ground truth depth:
MIT Media Lab Synthetic Light Field Archive:
Synthetic light fields including challenges like transparencies, occlusions and reflections
No ground truth disparities
Middlebury Multiview Stereo Datasets:
One 4D light field with ground truth depth for the center view
Additional 3D light fields with depth for two out of seven views
Large base lines and disparities, unsuitable for epipolar plane image analysis
Database Overview
dataset name category resolution GTD GTL
buddha
Blender 768×768×3 full
yes
horses
Blender 576×1024×3 full
yes
papillon
Blender 768×768×3 full
yes
stillLife
Blender 768×768×3 full
yes
buddha2
Blender 768×768×3 full
no
medieval
Blender 720×1024×3 full
no
monasRoom
Blender 768×768×3 full
no
couple
Gantry 898×898×3
cv
no
cube
Gantry 898×898×3
cv
no
maria
Gantry 926×926×3
cv
no
pyramide
Gantry 898×898×3
cv
no
statue
Gantry 898×898×3
cv
no
transparency
Gantry 926×926×3
cv
no
category: Blender (rendered synthetic dataset) or
Gantry (real-world dataset sampled using a single
moving camera).
resolution: spatial resolution of the views, all light
fields consist of 9x9 views.
GTD: completeness of ground truth depth data, either
cv (only center view) or full (all views).
GTL: indicates whether object segmentation data is
available.
Recorded with the gantry, transparent object with two ground truth depth layers:
Data Generation
Synthetic datasets
Real-world datasets
Bibliography
All datasets generated with the open source software Blender
For ground truth labels, objects rendered with fixed color
Plugin for light field rendering available on our web site
X
Vision, Modeling, and Visualization, Lugano, 2013
Nikon D800 digital camera mounted on
stepper-motor driven gantry
Objects pre-scanned with structured light
scanning device to obtain ground truth data
R. Bolles, H. Baker, and D. Marimont.
Epipolar-plane image analysis: An approach to determining structure from motion.
International Journal of Computer Vision, 1(1):7–55, 1987.
S. Gortler, R. Grzeszczuk, R. Szeliski, and M. Cohen.
The Lumigraph.
In Proc. SIGGRAPH, pages 43–54, 1996.