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Improving Geolocation by Combining
GPS with Image Analysis
F
bio Pinho, Alexandre Carvalho and Rui Carreira
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Abstract The Global Positioning System (GPS) provides geolocation to a
considerable number of applications in domains such as agriculture, commerce,
transportation and tourism. Operational factors such as signal noise or the lack of
direct vision from the receiver to the satellites, reduce the GPS geolocation accu-
racy. Urban canyons are a good example of an environment where continuous GPS
signal reception may fail. For some applications, the lack of geolocation accuracy,
even if happening for a short period of time, may lead to undesired results. For
instance, consider the damages caused by the failure of the geolocation system in a
city tour-bus transportation that shows location-sensitive data (historical/cultural
data, publicity) in its screens as it passes by a location. This work presents an
innovative approach for keeping geolocation accurate in mobile systems that rely
mostly on GPS, by using computer vision to help providing geolocation data when
the GPS signal becomes temporarily low or even unavailable. Captured frames of
the landscape surrounding the mobile system are analysed in real-time by a com-
puter vision algorithm, trying to match it with a set of geo-referenced images in a
precon
gured database. When a match is found, it is assumed that the mobile
system current location is close to the GPS location of the corresponding matched
point. We tested this approach several times, in a real world scenario, and the results
achieved evidence that geolocation can effectively be improved for scenarios where
GPS signal stops being available.
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