Sorting Holiday Photos without a GPS: What Can We Expect from Contents-Based Geo-spatial Image Tagging?

2010

Multimedia Systems

Self Cite

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.

Section: Experimental Evaluationmentioning

confidence: 99%

Where was that photo taken? Deriving geographical information from image collections based on temporal exposure attributes

2010

Multimedia Systems

Self Cite

“…Next, with the exception of beautiful sunrises and sunsets, it is uncommon to take direct photographs of the sun. Finally, although accurate horizon detection algorithms exist for small aircrafts flying at certain altitudes, it is much harder to determine the altitude from a photographer's perspective as he or she may be located in a city, in a valley or next to other tall objects that obstructs the view of the horizon [20].…”

Section: Direct Sun Elevation Measurementsmentioning

confidence: 99%

Determining the Geographical Location of Image Scenes based on Object Shadow Lengths

2010

J Sign Process Syst

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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.

“…The background for this work was the author's previous research on techniques for extracting geographical information from image collections [13][14][15][16] where the geographical information is extracted from the image meta data stored in the image EXIF headers [10,17,18]. This has for instance been applied to automatic tagging of images and providing summaries of collections in the form of image browsers for the blind [19].…”

Section: Ideationmentioning

confidence: 99%

A Configurable Photo Browser Framework for Large Image Collections

Human-Computer Interaction. Design and Development Approaches

2011

Self Cite

Abstract. 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.