Mastergradsoppgaver i teknologi - informatikk
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Mastergradsoppgaver i teknologi - informatikk
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Sundby, David (Master thesis; Mastergradsoppgave, 01-Jun-2011)[+][-]
Abstract: The widespread use of digital cameras and mobile phones, along with a rapidly growth of image sharing, challenges current image retrieval techniques. It is difficult for image retrieval system to find the semantic meaning of images based on human’s subjectivity and the size of current image databases makes it difficult to organize and search images. This thesis shows that information retrieval techniques can be used to reduce the search space of existing image collections, by creating collection summaries that holds only the most representative metadata from existing image collections. The representative metadata are metadata that are most distinguishing for the specific image collection. The system take advantage of the metadata available for images, which includes user provided tags, date/time, GPS coordinates, and metadata augmented by the system using already available metadata. Higher level representations of user provided terms are located and ensures that the system captures the most descriptive properties of the image collections. The system designed is able to produce collection summaries that capture properties of an image collection that support human’s natural perception as long as enough metadata are available. Also, the system increase the contextual understanding of images as long as date/time (of capture) and GPS coordinates is available for all or some of the images in the collection. The evaluation of the system indicates that grouping user provided terms into higher level representations is very useful for capturing the most important properties of an image collection. Also the evaluation expresses the usefulness of augmenting images with additional metadata and converting numeric metadata into readable terms. The comparisons made in the evaluation indicates that not only are the collection summaries similar to individual test users perception of image collections, but the summaries also includes more descriptive information of relevance. URI: http://hdl.handle.net/10037/3657 File(s) in this item: 2
source.zip (94.54Mb)thesis.pdf (3.098Mb) -
Gironi, Lorenzo (Master thesis; Mastergradsoppgave, 01-Jun-2011)[+][-]
Abstract: Hospital's communication infrastructure suffers from different types of common problems. Currently, this infrastructure relies mainly on the use of pagers which are devices particularly interruptive for the daily work of hospital's workers, and moreover they do not support context-awareness communication. Wireless phones are supposed to be a valid alternative to pagers and they can also be used to efficiently increase awareness between workers. Unfortunately, wireless phones can become more interruptive than pagers due to the synchronous communication channel they provide. The aim of this thesis is to propose an implementation of a context-aware solution, based on an Ascom/trixbox communication platform, which tries to overcome this problem. In particular it is specifically designed to balance availability and interruptions gained by using the Ascom wireless phones considering contextual information relating to the users carrying these devices, and it provides several features useful to increase awareness. This work is based on an on-going research project at the Norwegian Centre for Integrated Care and Telemedicine (NST), in collaboration with the University Hospital of Northern Norway (UNN) and Telenor. The focus of this project, named Context sensitive systems for mobile communication in hospitals is to design and develop context-sensitive interfaces, middleware and new interaction forms for mobile devices that support multi-modal communication. URI: http://hdl.handle.net/10037/3525 File(s) in this item: 1
thesis.pdf (1.499Mb) -
Johansen, Terje Andre (Master thesis; Mastergradsoppgave, Jun-2011)[+][-]
Abstract: In biology the introduction next generation technology is increasing the amount of data generated rapidly. New sequencing machines are able to produce terabytes of genomic data in days and in later years the cost of storing data has become higher than to produce it. With enormous amounts of data arrives great opportunities, but also new challenges; how should biologists analyze and interpret the results? Going through terabytes of data manually is time consuming, and is in reality not practical. Because of this bioinformatics are working together with computer scientists to create programs that can parse, integrate, analyze and visualize data in ways that can aid the biologist to extract novel biological knowledge from it. URI: http://hdl.handle.net/10037/3523 File(s) in this item: 1
thesis.pdf (2.724Mb) -
Leer, Erik Bræck (Master thesis; Mastergradsoppgave, Jun-2011)[+][-]
Abstract: Recently, television broadcasters such as the NRK and TV2 channels, have begun offering live internet television and movie archive along with their regular schedule, much like the known video archives such as Youtube and Vimeo. The amount of all television offered reduces the ability of the user to get an overview of the programs that are available at any given time, making the user will probably miss important events. Regular indexing engines for recommending does not generally work on media since it is hard to index media data. Tags and keywords describing a media le does only describe the whole le, making it difficult to use them for indexing and recommendation of specific scenes within the media. This thesis presents a text event detection system for discovering interesting events based on video subtitles. By performing textual analytics, our system is able to discover events that are not discoverable through regular syntactic search. We have, based on related work, extended algorithms used for discovering semantic relationships between different words. Also, we have experimented with several algorithm for capturing the essence of each sentence, relating the prominent sense of each sense towards the events. Our experiments illustrates how we can increase the accuracy of the algorithm used by performing a context exploration based on event keywords. The results shows that our system improved the base algorithm of the prototype by including more relevance methods like consecutive sentence similarity and similarity based on sentence internals. URI: http://hdl.handle.net/10037/3521 File(s) in this item: 1
thesis.pdf (1.736Mb) -
Holmstad, Øyvind (Master thesis; Mastergradsoppgave, 01-Jun-2011)[+][-]
Abstract: Real-time media rich applications rely on live streams of rich and accurate meta-data describing the video content to provide personal user experiences. Unfortunately, the general amount of video meta-data today is often limited to titles, synopsis and a few keywords. A wildly used approach for extraction of meta-data from video is computer vision. It has been developed a number of different video processing algorithms which can analyse and retrieve useful data from video. However, the computational cost of current computer vision algorithms is considerable. This thesis presents a software architecture that aims to enable real-time annotation of multiple live video streams. The architecture is intended for use within media rich applications where extraction of video semantics in real-time is necessary. Our conjecture was that staging video processing in levels will make room for a more scalable video annotation system. To evaluate our thesis we have developed the prototype runtime Árvdadus. Our experiments show that staged processing can decrease the computation time of meta-data extraction. The evaluation of the architecture suggests that the architecture is applicable in a wide range of domains where extraction of meta-data in real-time is necessary URI: http://hdl.handle.net/10037/3520 File(s) in this item: 1
thesis.pdf (1.715Mb)
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