Publications in Scientific Journals:

M. Doneus, G. Verhoeven, M. Fera, C. Briese, M. Kucera, W. Neubauer:
"From Deposit to Point Cloud - a Study of Low-Cost Computer Vision Approaches for the Straightforward Documentation of Archaeological Excavations";
Geoinformatics CTU FCE, 6 (2011), 8 pages.

English abstract:
Stratigraphic archaeological excavations demand high-resolution documentation techniques for 3D
recording. Today, this is typically accomplished using total stations or terrestrial laser scanners. This paper
demonstrates the potential of another technique that is low-cost and easy to execute. It takes advantage of software
using Structure from Motion (SfM) algorithms, which are known for their ability to reconstruct camera pose and threedimensional
scene geometry (rendered as a sparse point cloud) from a series of overlapping photographs captured by a
camera moving around the scene. When complemented by stereo matching algorithms, detailed 3D surface models can
be built from such relatively oriented photo collections in a fully automated way. The absolute orientation of the model
can be derived by the manual measurement of control points. The approach is extremely flexible and appropriate to
deal with a wide variety of imagery, because this computer vision approach can also work with imagery resulting from
a randomly moving camera (i.e. uncontrolled conditions) and calibrated optics are not a prerequisite. For a few years,
these algorithms are embedded in several free and low-cost software packages. This paper will outline how such a
program can be applied to map archaeological excavations in a very fast and uncomplicated way, using imagery shot
with a standard compact digital camera (even if the images were not taken for this purpose). Archived data from
previous excavations of VIAS-University of Vienna has been chosen and the derived digital surface models and
orthophotos have been examined for their usefulness for archaeological applications. The absolute georeferencing of
the resulting surface models was performed with the manual identification of fourteen control points. In order to
express the positional accuracy of the generated 3D surface models, the NSSDA guidelines were applied.
Simultaneously acquired terrestrial laser scanning data - which had been processed in our standard workflow - was
used to independently check the results. The vertical accuracy of the surface models generated by SfM was found to be
within 0.04 m at the 95 % confidence interval, whereas several visual assessments proved a very high horizontal
positional accuracy as well.

excavation, computer vision, low-cost, 3D single-surface recording, orthophoto

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.