Here, we provide interested researchers a real-world multi-view test data set
captured in the blue-c portals.
The data is meant to be used
for testing reconstruction/rendering algorithms based on multi-view
video sequences with consideration of noise and other capturing
device errors. Furthermore, it can be used for testing streaming and
compression techniques since we are also providing depth maps as
calculated by a shape-from-silhouettes method.
The set consists of frame sequences rendered from 16
different camera views located in a hemisphere around the scene, background
images, segmentation masks, depth images, and camera parameters. The
recorded scene contains different humans performing various motions, ranging
from simple and slow movements to kicks and punchs of a Kung-Fu fighter. The
sequences have different lengths and are recorded at
different acquisition frame rates. Each frame is saved as a 640 x 480 image.
Here is an illustration of the blue-c portal at ETH Hönggerberg
where all sequences are captured. The numbers indicate the camera
nodes (i.e., arctic1 - arctic16).
Quicktime VR inside-out:
Test sequences are available upon request. Please write to wwwgraphinf.ethz.ch for more information.
Calibration data from our
self-calibration procedure can be found here. You can also do your own calibration by downloading the calibration sequence. The parameters are
stored according to:
|Files (e.g., "arctic3.cal")
||Projection matrix (3x3) & camera center (3x1) for
camera xxx, incl. extrinsic & intrinsic parameters. Can be
directly used to calculate rays from the camera center through
pixels in the image plane.
||3x4 euclidean projection matrix for camera
xxx which encodes all linear
parameters. You can use function ./MultiCamValidation/CoreFunctions/P2KRtC.m
multi-camera self-calibration package to decompose it into
the intrinsic parameters in 3x3 K matrix, rotation matrix R and
translation vector t, as well as the position of the camera
center C in the common world coordinate system.
||Parameters needed for undoing radial distortion
for camera xxx.
Intrinsic parameters in 3x3 K matrix, and image distortion
coefficients (only radial distortions!) in 4x1 vector kc. They should
be directly applicable in the OpenCV implementation of the
undoing non-linear distortion.
We also provide graphical outputs for understanding the setup and
calibration accuracy (which is mostly
around 0.2 pixels reprojection error).
Download calibration data