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

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

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

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

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

Exploring Circular Hough Transforms for Detecting Hand Feature Points in Noisy Images from Ghost-Circle Patterns

acceptedVersio

Measuring 2D:4D finger length ratios with Smartphone Cameras

Finger length ratios have received much attention among researchers as the 2D:4D ratio has been linked to several physical and mental characteristics. This study explores the feasibility of using a Smartphone as an instrument for measuring finger length ratios. The approach taken in this study is to use the Smartphone camera to take freehand photos of the hand which is subsequently subjected to image analysis. Measurement procedures include hand near and far from the body, palms up or down, or hands in mid air versus hands resting on a flat surface. Experimental evaluations show that the most accurate measurements are achieved by resting the hand on a surface with the palm facing up. These results are comparable to those achieved with conventional procedures with an error of 1%