74 research outputs found
From Deposit to Point Cloud – a Study of Low-Cost Computer Vision Approaches for the Straightforward Documentation of Archaeological Excavations
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 ima ges 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 a bsolute 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
Big Earth Data for Cultural Heritage in the Copernicus Era
Digital data is stepping in its golden age characterized by an increasing
growth of both classical and emerging big earth data along with trans- and multidisciplinary
methodological approaches and services addressed to the study, preservation
and sustainable exploitation of cultural heritage (CH). The availability of new
digital technologies has opened new possibilities, unthinkable only a few years ago
for cultural heritage. The currently available digital data, tools and services with
particular reference to Copernicus initiatives make possible to characterize and
understand the state of conservation of CH for preventive restoration and opened up
a frontier of possibilities for the discovery of archaeological sites from above and
also for supporting their excavation, monitoring and preservation. The different
areas of intervention require the availability and integration of rigorous information
from different sources for improving knowledge and interpretation, risk assessment
and management in order to make more successful all the actions oriented to the
preservation of cultural properties. One of the biggest challenges is to fully involve
the citizen also from an emotional point of view connecting “pixels with people”
and “bridging” remote sensing and social sensing
Automated Classification of Airborne Laser Scanning Point Clouds
Making sense of the physical world has always been at the core of mapping. Up
until recently, this has always dependent on using the human eye. Using
airborne lasers, it has become possible to quickly "see" more of the world in
many more dimensions. The resulting enormous point clouds serve as data sources
for applications far beyond the original mapping purposes ranging from flooding
protection and forestry to threat mitigation. In order to process these large
quantities of data, novel methods are required. In this contribution, we
develop models to automatically classify ground cover and soil types. Using the
logic of machine learning, we critically review the advantages of supervised
and unsupervised methods. Focusing on decision trees, we improve accuracy by
including beam vector components and using a genetic algorithm. We find that
our approach delivers consistently high quality classifications, surpassing
classical methods
Using airborne LiDAR Survey to explore historic-era archaeological landscapes of Montserrat in the eastern Caribbean
This article describes what appears to be the first archaeological application of airborne LiDAR survey to historic-era landscapes in the Caribbean archipelago, on the island of Montserrat. LiDAR is proving invaluable in extending the reach of traditional pedestrian survey into less favorable areas, such as those covered by dense neotropical forest and by ashfall from the past two decades of active eruptions by the Soufrière Hills volcano, and to sites in localities that are inaccessible on account of volcanic dangers. Emphasis is placed on two aspects of the research: first, the importance of ongoing, real-time interaction between the LiDAR analyst and the archaeological team in the field; and second, the advantages of exploiting the full potential of the three-dimensional LiDAR point cloud data for purposes of the visualization of archaeological sites and features
ADVANCING THE DOCUMENTATION OF BURIED ARCHAEOLOGICAL LANDSCAPES
The future demands on professional archaeological prospection will be its ability to cover large areas in a time and cost efficient
manner with very high spatial resolution and accuracy. The objective of the 2010 in Vienna established Ludwig Boltzmann Institute
for Archaeological Prospection and Virtual Archaeology, in collaboration with its nine European partner organisations, is the
advancement of the state-of-the-art. This goal will be achieved by focusing on the development of remote sensing, geophysical
prospection and virtual reality applications. Main focus will be placed on novel integrated interpretation approaches combining
cutting-edge near-surface prospection methods with advanced computer science
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