112,428 research outputs found
Efficient Algorithmic Techniques for Several Multidimensional Geometric Data Management and Analysis Problems
In this paper I present several novel, efficient, algorithmic techniques for solving some multidimensional geometric data management and analysis problems. The techniques are based on several data structures from computational geometry (e.g. segment tree and range tree) and on the well-known sweep-line method.geometric data management, computational geometry, sweep-line method
A storage and access architecture for efficient query processing in spatial database systems
Due to the high complexity of objects and queries and also due to extremely
large data volumes, geographic database systems impose stringent requirements on their
storage and access architecture with respect to efficient query processing. Performance
improving concepts such as spatial storage and access structures, approximations, object
decompositions and multi-phase query processing have been suggested and analyzed as
single building blocks. In this paper, we describe a storage and access architecture which
is composed from the above building blocks in a modular fashion. Additionally, we incorporate
into our architecture a new ingredient, the scene organization, for efficiently
supporting set-oriented access of large-area region queries. An experimental performance
comparison demonstrates that the concept of scene organization leads to considerable
performance improvements for large-area region queries by a factor of up to 150
Query processing of geometric objects with free form boundarie sin spatial databases
The increasing demand for the use of database systems as an integrating
factor in CAD/CAM applications has necessitated the development of database
systems with appropriate modelling and retrieval capabilities. One essential
problem is the treatment of geometric data which has led to the development of
spatial databases. Unfortunately, most proposals only deal with simple geometric
objects like multidimensional points and rectangles. On the other hand, there has
been a rapid development in the field of representing geometric objects with free
form curves or surfaces, initiated by engineering applications such as mechanical
engineering, aviation or astronautics. Therefore, we propose a concept for the realization
of spatial retrieval operations on geometric objects with free form
boundaries, such as B-spline or Bezier curves, which can easily be integrated in
a database management system. The key concept is the encapsulation of geometric
operations in a so-called query processor. First, this enables the definition of
an interface allowing the integration into the data model and the definition of the
query language of a database system for complex objects. Second, the approach
allows the use of an arbitrary representation of the geometric objects. After a
short description of the query processor, we propose some representations for free
form objects determined by B-spline or Bezier curves. The goal of efficient query
processing in a database environment is achieved using a combination of decomposition
techniques and spatial access methods. Finally, we present some experimental
results indicating that the performance of decomposition techniques is
clearly superior to traditional query processing strategies for geometric objects
with free form boundaries
Towards cost-efficient prospection and 3D visualization of underwater structures using compact ROVs
The deployment of Remotely Operated Vehicles (ROV) for underwater prospection and 3D visualization has grown significantly in civil applications for a few decades. The demand for a wide range of optical and physical parameters of underwater environments is explained by an increasing complexity of the monitoring requirements of these environments. The prospection of engineering constructions (e.g. quay walls or enclosure doors) and underwater heritage (e.g. wrecks or sunken structures) heavily relies on ROV systems. Furthermore, ROVs offer a very flexible platform to measure the chemical content of the water. The biggest bottleneck of currently available ROVs is the cost of the systems. This constrains the availability of ROVs to a limited number of companies and institutes. Fortunately, as with the recent introduction of cost-efficient Unmanned Aerial Vehicles on the consumer market, a parallel development is expected for ROVs. The ability to participate in this new field of expertise by building Do It Yourself (DIY) kits and by adapting and adding on-demand features to the platform will increase the range of this new technology.
In this paper, the construction of a DIY OpenROV kit and its implementation in bathymetric research projects are elaborated. The original platform contains a modified webcam for visual underwater prospection and a Micro ElectroMechanical System (MEMS) based depth sensor, allowing relative positioning. However, the performance of the standard camera is limited and an absolute positioning system is absent. It is expected that 3D visualizations with conventional photogrammetric qualities are limited with the current system. Therefore, modifications to improve the standard platform are foreseen, allowing the development of a cost-efficient underwater platform. Preliminary results and expectations on these challenges are reported in this paper
The combination of spatial access methods and computational geometry in geographic database systems
Geographic database systems, known as geographic information systems (GISs) particularly among non-computer scientists, are one of the most important applications of the very active research area named spatial database systems. Consequently following the database approach, a GIS hag to be seamless, i.e. store the complete area of interest (e.g. the whole world) in one database map. For exhibiting acceptable performance a seamless GIS hag to use spatial access methods. Due to the complexity of query and analysis operations on geographic objects, state-of-the-art computational geomeny concepts have to be used in implementing these operations. In this paper, we present GIS operations based on the compuational geomeny technique plane sweep. Specifically, we show how the two ingredients spatial access methods and computational geomeny concepts can be combined fĂŒr improving the performance of GIS operations. The fruitfulness of this combination is based on the fact that spatial access methods efficiently provide the data at the time when computational geomeny algorithms need it fĂŒr processing. Additionally, this combination avoids page faults and facilitates the parallelization of the algorithms.
Multi-Step Processing of Spatial Joins
Spatial joins are one of the most important operations for combining spatial objects of several relations. In this paper, spatial join processing is studied in detail for extended spatial objects in twodimensional data space. We present an approach for spatial join processing that is based on three steps. First, a spatial join is performed on the minimum bounding rectangles of the objects returning a set of candidates. Various approaches for accelerating this step of join processing have been examined at the last yearâs conference [BKS 93a]. In this paper, we focus on the problem how to compute the answers from the set of candidates which is handled by
the following two steps. First of all, sophisticated approximations
are used to identify answers as well as to filter out false hits from
the set of candidates. For this purpose, we investigate various types
of conservative and progressive approximations. In the last step, the
exact geometry of the remaining candidates has to be tested against
the join predicate. The time required for computing spatial join
predicates can essentially be reduced when objects are adequately
organized in main memory. In our approach, objects are first decomposed
into simple components which are exclusively organized
by a main-memory resident spatial data structure. Overall, we
present a complete approach of spatial join processing on complex
spatial objects. The performance of the individual steps of our approach
is evaluated with data sets from real cartographic applications.
The results show that our approach reduces the total execution
time of the spatial join by factors
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