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Title
The 3rd ISPRS Workshop on Dynamic and Multi-Dimensional GIS & the 10th Annual Conference of CPGIS on Geoinformatics
Author
Chen, Jun

ISPRS, Vol.34, Part 2W2, “Dynamic and Multi-Dimensional GIS’’, Bangkok, May 23-25, 2001
The result is a list of co-ordinates structured according to the
order of the faces and order of the nodes in a face. To create the
VRML file, the data set obtained with these queries has to be
further structured according the VRML model. In our example,
two options are possible to represent the faces constructing the
POLYHEDRON 23 in VRML, i.e. they can be stored as individual
faces or as a part of one polyhedron. The first option is simpler
and can be derived directly from the SQL query. The second
representation requires control of duplicated co-ordinates and
the correct ordering of the corresponding co-ordinates in the
description of the faces (i.e. in the VRML node coordlndex).
Currently, we concentrated on development of operators that
create a VRML file consisting of objects (i.e. not individual
faces). Since standard SQL statements cannot perform this
operator, the computations have to be completed with the help
of a host language (PL/SQL, C++, Java). At this stage, we have
used PL/SQL, i.e. the script language provided by Oracle.
A number of tests aimed at clarification of the best mapping and
fastest operators to retrieve the needed data. For the purpose
the first tree mappings discussed in the paper are implemented
and populated with data. The corresponding VRML creators are
tested for performance. Although the data structure is at very
initial stage, the first results are very encouraging: 20 000 faces
(part of 1600 buildings) can be retrieved in less then 23 seconds
for representation with nested tables and less then a second for
the relational representation and object-oriented views. The
conditions of the test and the data sets are reported and
discussed in more details in [17]. In principal, we expect less
data to be extracted for rendering, i.e. the objects that are visible
only from the current position of the user. These data are
estimated in the range between 50 and 5000 faces if spatial
search is applied. This is indication for a possible further
improvement of the obtained results.
7 CONCLUSIONS
We have presented a 3D topological structure that provides data
for a real time application i.e. serves two tasks (pose
determination and rendering of virtual objects) that require real
time commuting. The proposed structure maintains four
abstractions of geometric representation (the ones mostly
employed in 3D modelling) based on two constructive elements
(faces and nodes). To be able to provide “cheap” details in terms
of line features, the model incorporates non-topologically
organised data, i.e. lines. Explicit relationship links a set of lines
to a face. To be able to achieve the required accuracy and to
build the 3D topology, a number of 3D reconstruction methods
are applied. The model is implemented in relational database
Oracle utilising relational and object-relational mappings.
Several operators to create a VRML file are created and tested.
The experiments clearly show that a 3D topological model can
be adopted for an augmented reality application. The
performance of the mappings in relational database drops
bellow the required 6 seconds. The methods utilised in the 3D
reconstruction ensure accuracy of few decimetres that is agreed
to be sufficient for the positioning system. Therefore we consider
the results reported in this paper a successful step toward a 3D
GIS supplying data for a real time application.
Still more experiments are needed to clarify the relational
mapping that will assure the best performance. Currently, the
SQL queries are executed from the Oracle high-level language
that cannot be integrated in the UbiCom architecture, i.e. C++
modules have to be developed and further tested. Location and
efficient spatial search in such large databases can not be
performed without appropriate spatial indexing. One of the
directions for further research within the project is related to
developing a set of specific operations than will reduce the
amount of data transmitted to the vision system. Examples of
such operators are determination of the area of interest (using
approximate positioning obtained by the mobile equipment),
back-face culling (to eliminate invisible faces) and a variety of
line filters for retrieval of line features.
References
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BIOGRAPHY
Siyka Zlatanova:
MSc degree at the University of Architecture, Civil Engineering
and Geodesy, Sofia, Bulgaria in 1983 (Geodesy and
Photogrammetry). PhD degree at the Graz University of
Technology, Graz, Austria. Currently, a post-doctoral researcher
at the Delft University of Technology, Delft, The Netherlands.
Research field: Spatial Data Handling, 3D topology, 3D object
reconstruction and visualisation.