Geo-Services and Computer Vision for Object Awareness in Mobile System Applications View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2007-01-01

AUTHORS

Patrick Luley , Lucas Paletta , Alexander Almer , Mathias Schardt , Josef Ringert

ABSTRACT

In recent years, location and context aware systems have been presented for the indexing and annotation of both location and user state relevant information to the user. These systems were mostly based on georeferencing from GPS signals, and driven by changes of the system state in dependence on situations that impact the overall system performance (user position, energy consumption, responsiveness, etc.). In this chapter we focus attention on a completely innovative aspect of contextual indexing for mobile system applications. We claim that the application of geo-services and vision based sensing enables systems to determine object characteristics information that can be used for semantic indexing of information and thereby provide an innovative quality of service.Computer vision can be used to extract object information, such as the identity of buildings (Figure 1), information signs, people, etc., and thereby enable object based indexing which can finally be applied to extract a semantic description of the environment. Geo-services are mandatory to support vision based object recognition and semantic indexing in several ways. Firstly, location based sensing provides information about the geo-reference of objects in the field of view, it reduces the number of possible object hypotheses and therefore can dramatically simplify the complexity of object recognition. Secondly, vision provides an estimate of the user position from the geo-referenced object information. Geo-services can use this to reason more efficiently about a current object and user position. More... »

PAGES

291-300

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-36728-4_22

DOI

http://dx.doi.org/10.1007/978-3-540-36728-4_22

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1040158832


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