262 research outputs found
Towards calibration-free geo-localization of stationary outdoor webcams
This study proposes two strategies for determining the approximate
geographical location of outdoor webcams based on time-series comprising
regularly sampled images. The strategies require an accurate account of
universal time and the date to be known, then the intensity of the images
are used to estimate the sunrise and sunset times. Given accurate sunrise
and sunset times a celestial model can be used to extract the latitude and
longitude of the webcam. Webcams vary in quality, dynamic pixel depth
and sensitivity to light. Two strategies are therefore proposed for avoiding
the need to perform calibration. The first technique involves normalizing
and noise-damping the image intensity measurements. The second technique
employs a self-normalizing brightness ratio. The brightness ratio is computed
from the overall brightness of the upper part of the image in relation to the
bottom part. During day the sky is much brighter than the ground, while
at night the sky is much darker than the ground if the ground is lit up.
Experiments demonstrate that the intensity normalization strategy is the most
robust and it is capable of determining the geographical location of webcams
with an accuracy of approximately 2 degrees
Unsupervised and Fast Continent Classification of Digital Image Collections using Time
Advances in storage capacity means that digital
cameras can store huge collections of digital photographs.
Typically such images are given non-descriptive filenames names
such as a unique identifier, often an integer. Consequently it is
time-consuming and difficult to browse and retrieve images from
large collections especially on small consumer electronics devices.
A strategy for classifying images into geographical regions is
presented which allows images to be coarsely sorted into the
continent where they were taken. The strategy employs patterns
in the time-stamps of images to identify events such as holiday
and individual days, and to estimate the approximate longitude
where the photographs were taken. Experimental evaluations
demonstrate that the continent is correctly estimated for 89 % of
the images in arbitrary collections and that the longitude is
estimated with a mean error of 27.5 degrees. The strategy is
relatively straightforward to implement, also in hardware, and
computationally inexpensive
A Configurable Photo Browser Framework for Large Image Collections
Image collections are growing at an exponential rate due to the wide
availability of inexpensive digital cameras and storage. Current browsers
organize photos mostly chronologically, or according to manual tags. For very
large collections acquired over several years it can be difficult to locate a
particular set of images – even for the owner. Although our visual memory is
powerful, it is not always easy to recall all of one’s images. Moreover, it can be
very time consuming to find particular images in other peoples image
collections. This paper presents a prototype image browser and a plug-in pattern
that allows classifiers to be implemented and easily integrated with the image
browser such that the user can control the characteristics of the images that are
browsed and irrelevant photos are filtered out. The filters can both be content
based and based on meta-information. The current version is only employs
meta-information which means that large image collections can be indexed
efficiently
On the Truthfulness of Petal Graphs for Visualisation of Data
A petal graph is an aesthetically attractive and applauded tool for visualising parameter sets. For instance, petal graphs are often used by Norwegian policy makers and decision makers in higher education as the Ministry of Education and Research relies on petal graphs in their reports. This study argues that petal graphs are prone to misinterpretation. It is challenging to interpret a petal graph in general, it is hard to compare two or more petal graphs and this study demonstrates that the physical characteristics of petal graphs can be incorrect in terms of the parameters on display. This study concludes that the use of petal graphs should be abolished and that other visualisation techniques to be used instead. Several alternatives are suggested
Determining the Geographical Location of Image Scenes based on Object Shadow Lengths
Many studies have addressed various applications
of geo-spatial image tagging such as image retrieval,
image organisation and browsing. Geo-spatial image
tagging can be done manually or automatically with GPS
enabled cameras that allow the current position of the
photographer to be incorporated into the meta-data of an
image. However, current GPS-equipment needs certain time
to lock onto navigation satellites and these are therefore not
suitable for spontaneous photography. Moreover, GPS units
are still costly, energy hungry and not common in most
digital cameras on sale. This study explores the potential of,
and limitations associated with, extracting geo-spatial
information from the image contents. The elevation of the
sun is estimated indirectly from the contents of image
collections by measuring the relative length of objects and
their shadows in image scenes. The observed sun elevation
and the creation time of the image is input into a celestial
model to estimate the approximate geographical location of
the photographer. The strategy is demonstrated on a set of
manually measured photographs
A Non-Visual Photo Collection Browser based on Automatically Generated Text Descriptions
This study presents a textual photo collection
browser that automatically and quickly analyses large personal
photo collections and produces textual reports that can be
accessed by blind users using either text-to-speech or Braille
output devices. The textual photo browser exploits recent
advances in image collection analysis and the strategy does not
rely on manual image tagging. The reports produced by the
textual image browser gives the user a gist about where, when
and what the photographer was doing in the form of a story.
Although yet crude, the strategy can give blind users a
valuable overview about the contents of large image collections
and individual images which otherwise are totally inaccessible
without vision
An Energy Efficient Localization Strategy for Outdoor Objects based on Intelligent Light-Intensity Sampling
A simple and low cost strategy for implementing pervasive objects that identify and track their own geographical location is proposed. The strategy, which is not reliant on any GIS infrastructure such as GPS, is realized using an electronic artifact with a built in clock, a light sensor, or low-cost digital camera, persistent storage such as flash and sufficient computational circuitry to make elementary trigonometric computations. The object monitors the lighting conditions and thereby detects and tracks the sunrise and sunset times. By the means of a simple celestial model an estimate of the geographical position of the object can be made. An intelligent light sampling method is proposed allowing the object to sleep most of the time and hence save battery power. The strategy is energy efficient and the speed of convergence can be adjusted as a function of the energy consumed. Objects employing the method can therefore operate for long times without recharging their batteries. The strategy has applications in mobile sensor networks where nodes need to log geographical information, sensing equipment such as floating buoyancies, or pervasive technologies in need of geo-spatial information such as digital cameras, mobile devices, etc
Exploring Circular Hough Transforms for Detecting Hand Feature Points in Noisy Images from Ghost-Circle Patterns
acceptedVersio
Where was that photo taken? : deriving geographical information from image collections based on temporal exposure attributes
This paper demonstrates a novel strategy for
inferring approximate geographical information from the
exposure information and temporal patterns of outdoor
images in image collections. Image exposure is reliant on
light and most photographs are therefore taken in daylight
which again depends on the position of the sun. Clearly, the
sun results in different lighting conditions at different
geographical location and at different times of the day, and
hence the observed intensity patterns can be used to deduce
the approximate location of the photographer at the time
the photographs were taken. Images taken inside or at night
are temporally connected to the daylight images and the
geographical information can therefore be transferred to
related ‘‘dark’’ photographs. The strategy is efficient as it
only considers meta information and not image contents.
Large databases can therefore be indexed efficiently.
Experimental results demonstrate that the current approach
yields a longitudinal error of 15.7 and a latitudinal error of
30.5 for authentic image collections comprising a mixture
of outdoor and indoor images. The strategy determined the
correct hemisphere in all the tests. Although not as accurate
as GPS receiver, the geographical information is sufficiently
detailed to be useful. Applications include
improved image retrieval, image browsing and automatic
image tagging. The strategy does not require a GPS
receiver and can be applied to the existing digital image
collections
Effects of common keyboard layouts on physical effort : implications for kiosks and Internet banking
This study investigates the effect common keyboard layouts
have physical effort. First, alphabetic keyboard layouts are
experimentally compared to the QWERTY layout. Second, the number
row often found on QWERTY keyboards are experimentally compared
to numeric keypad layout. Our study shows that users operate more
effectively using a QWERTY layout than an alphabetical layout.
Moreover, users operate more effectively using a numeric keypad
compared to a row of number keys. Implications for two important
application areas in society, namely touch-based self-service kiosks
and numeric input in context of Internet banking are discussed
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