Assisted Navigation in Large Information Spaces

camera planning;navigation;information visualization;multidimensional visualization;scientific visualization;graph;information spaces

Dennis, Brent Moorman ; Dr. Carla Savage, Committee Member,Dr. Christopher G. Healey, Committee Chair,Dr. Robert St. Amant, Committee Member,Dennis, Brent Moorman ; Dr. Carla Savage ; Committee Member ; Dr. Christopher G. Healey ; Committee Chair ; Dr. Robert St. Amant ; Committee Member

University:North Carolina State University

关键词: camera planning;    navigation;    information visualization;    multidimensional visualization;    scientific visualization;    graph;    information spaces;   

Others  :  https://repository.lib.ncsu.edu/bitstream/handle/1840.16/1637/etd.pdf?sequence=1&isAllowed=y

美国|英语

来源: null

【 摘 要 】

With the advent of computers and more sophisticated electronics, scientists can now collect massive amount of information.The increasing emph{size} and emph{dimensionality} of thesedatasets makes them challenging to visualize in an effective manner. Visualizations must show the global structure of spatial relationships within the dataset while simultaneously representing the local detail of each data element being visualized.Techniques in information visualization provide views of the dataset at multiple scales allowing the user to visualize large numbers of data elements.Unfortunately, these techniques often do not address the problems of displaying multidimensional datasets.Multidimensional visualizations use color, texture, and other visual features to represent the values of multiple attributes at a single spatial location.However, these techniques do not address how to visualize large numbers of data elements.Visualizations of datasets with large sizes and high dimensionalities are often forced to omit data elements from the current view.This thesis proposes to combine ideas from information and multidimensional visualization with a emph{navigation assistant} to help users identify and explore areas of interest within their data. The assistant locates data elements that are potentially "interesting" to the user, clusters them into spatial regions, and constructs underlying graph structures to connect the regions and elements they contain.Using graph traversal algorithms, optimal viewpoint construction, and camera planning techniques, the navigation assistant builds informative animated tours of these regions.In this way, the assistant provides an effective tool for exploring a dataset.