This directory tree contains data that can be used as input for algorithms that perform 3D reconstruction from image features that have been tracked along a sequence.Three short sequences have been acquired and visible objects have been selected. Some 3D points on each objects have been tracked and the data stored in files.
We hope that this data will be useful to people testing reconstruction algorithms : using these files should be easier than acquiring images and tracking points.
This dataset consists in :
Each of the following directories contains data relevant to a single image
sequence :
Each directory contains a SEQUENCE/image subdirectory containing the "tif" images, as well as at least one SEQUENCE/OBJECT directory that contains the data pertaining to a given object :
The above directories contain at the following files :
Important Note : the coordinates are taken from bottom to top, left to right. In order to obtain a direct frame whose Z-axis points forward (towards the object), one of the coordinate axes in the image plane must be inverted. It is customary to invert the Y-axis, so that coordinates are taken from top to bottom.
One assumes that the observations u0(2*f-i,p), for f=1..N, p=1..P and i=1..2, are obtained through the perspective projection model. We first define the simplified projection model :
a(3*f-i,:)*(x(:,p)+t(3*f-2:3*f)) V(2*f-i,p) = -------------------------------- a(3*f,:) *(x(:,p)+t(3*f-2:3*f))
This is the projection of the 3D point on the image plane, assuming that the focal length is 1, the sensor is skewless, the aspect ratio is 1 and the coordinates are taken relative to the principal point.
The full projection model also integates the skew, aspect ratio, focal length, principal point and noise.
u0(2*f-[1,0],p) = exp(-k(5)) * ( K * V(2*f-[1,0],p) + C ) + Noise
Where
K = [ 1 0 ] Represents the skew of the [ 10*k(1) 10*k(2)+1 ] sensor and its aspect ratio. and C = 10*[ k(3) ] Is the image center [ k(5) ] ("principal point")
The focal length of the camera is exp(k(5)).
More details can be found in many documents on computer vision, for example, at CVonline.
This data has been produced within the INCO - Copernicus Project 960174 (VIRTUOUS)
The data in this directory may contain some errors. Please contact Etienne Grossmann for any comments and questions.