66,772 research outputs found
Lifting GIS Maps into Strong Geometric Context for Scene Understanding
Contextual information can have a substantial impact on the performance of
visual tasks such as semantic segmentation, object detection, and geometric
estimation. Data stored in Geographic Information Systems (GIS) offers a rich
source of contextual information that has been largely untapped by computer
vision. We propose to leverage such information for scene understanding by
combining GIS resources with large sets of unorganized photographs using
Structure from Motion (SfM) techniques. We present a pipeline to quickly
generate strong 3D geometric priors from 2D GIS data using SfM models aligned
with minimal user input. Given an image resectioned against this model, we
generate robust predictions of depth, surface normals, and semantic labels. We
show that the precision of the predicted geometry is substantially more
accurate other single-image depth estimation methods. We then demonstrate the
utility of these contextual constraints for re-scoring pedestrian detections,
and use these GIS contextual features alongside object detection score maps to
improve a CRF-based semantic segmentation framework, boosting accuracy over
baseline models
Semantic Web Tools and Decision-Making
Semantic Web technologies are intertwined with decision-making
processes. In this paper the general objectives of the semantic web tools are reviewed
and characterized, as well as the categories of decision support tools, in
order to establish an intersection of utility and use. We also elaborate on actual
and foreseen possibilities for a deeper integration, considering the actual implementation,
opportunities and constraints in the decision-making context.info:eu-repo/semantics/publishedVersio
SEEING THE UNSEEN: DELIVERING INTEGRATED UNDERGROUND UTILITY DATA IN THE UK
In earlier work we proposed a framework to integrate heterogeneous geospatial utility data in the UK. This paper provides an update on the techniques used to resolve semantic and schematic heterogeneities in the UK utility domain. Approaches for data delivery are discussed, including descriptions of three pilot projects and domain specific visualization issues are considered. A number of practical considerations are discussed that will impact on how any implementation architecture is derived from the integration framework. Considerations of stability, security, currency, operational impact and response time can reveal a number of conflicting constraints. The impacts of these constraints are discussed in respect of either a virtual or materialised delivery system. 1
Semantic web and decision support systems
Semantic Web technologies are intertwined with the decision-making process. In this paper the general objectives of the semantic web tools are reviewed and characterized, as well as the categories of decision support tools, in order to establish an intersection of utility and use. We also elaborate on actual and foreseen possibilities for a deeper integration, considering the actual implementation, opportunities and constraints within the context of decision-making. We conclude that a broader or generalized Semantic Web integration in the decision support community is still a work in progress and much remains to be done.info:eu-repo/semantics/publishedVersio
Flexible provisioning of Web service workflows
Web services promise to revolutionise the way computational resources and business processes are offered and invoked in open, distributed systems, such as the Internet. These services are described using machine-readable meta-data, which enables consumer applications to automatically discover and provision suitable services for their workflows at run-time. However, current approaches have typically assumed service descriptions are accurate and deterministic, and so have neglected to account for the fact that services in these open systems are inherently unreliable and uncertain. Specifically, network failures, software bugs and competition for services may regularly lead to execution delays or even service failures. To address this problem, the process of provisioning services needs to be performed in a more flexible manner than has so far been considered, in order to proactively deal with failures and to recover workflows that have partially failed. To this end, we devise and present a heuristic strategy that varies the provisioning of services according to their predicted performance. Using simulation, we then benchmark our algorithm and show that it leads to a 700% improvement in average utility, while successfully completing up to eight times as many workflows as approaches that do not consider service failures
A framework for utility data integration in the UK
In this paper we investigate various factors which prevent utility knowledge from being
fully exploited and suggest that integration techniques can be applied to improve the
quality of utility records. The paper suggests a framework which supports knowledge
and data integration. The framework supports utility integration at two levels: the
schema and data level. Schema level integration ensures that a single, integrated geospatial
data set is available for utility enquiries. Data level integration improves utility data
quality by reducing inconsistency, duplication and conflicts. Moreover, the framework
is designed to preserve autonomy and distribution of utility data. The ultimate aim of
the research is to produce an integrated representation of underground utility infrastructure
in order to gain more accurate knowledge of the buried services. It is hoped that
this approach will enable us to understand various problems associated with utility data,
and to suggest some potential techniques for resolving them
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