Browsing by Author "Höferlin, Markus Johannes"

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    Video visual analytics
    (2013) Höferlin, Markus Johannes; Weiskopf, Daniel (Prof. Dr.)
    The amount of video data recorded world-wide is tremendously growing and has already reached hardly manageable dimensions. It originates from a wide range of application areas, such as surveillance, sports analysis, scientific video analysis, surgery documentation, and entertainment, and its analysis represents one of the challenges in computer science. The vast amount of video data renders manual analysis by watching the video data impractical. However, automatic evaluation of video material is not reliable enough, especially when it comes to semantic abstraction from the video signal. In this thesis, the visual analytics methodology is applied to the video domain to combine the complementary strengths of human cognition and machine processing. After depicting the challenges of scalable video analysis, a video visual analytics pipeline is proposed that relies on stream processing for scalability. The proposed video visual analytics pipeline consists of six stages that are processed successively--data stream selection, manipulation, feature extraction, filtering, relevance measure, and visualization--before the results are presented to the human analysts. The human analysts can interact and modify each of these stages iteratively. To support sense-making, the human analysts can directly integrate and organize reasoning artifacts into a reasoning sandbox. For the video visual analytics pipeline, various methods for the different stages are introduced that address data scalability, task scalability, and situational awareness. This work focuses mainly on the filtering and visualization stages, but provides reviews and discussions of techniques for the other stages as well. In the filtering stage, four interaction guidelines--easy-to-use filter definition, confidence-incorporated filter definition, decision-guided filter definition, and filter feedback--are defined and applied to formulate filters by properties, by sketch, or by example. Due to the suitability of trajectories for filtering, a configurable similarity metric for trajectories is introduced that allows combining different facets (features) with different similarity measures. Besides a survey on video visualization methods, the thesis contributes to the visualization stage by methods for fast-forward video visualization and hierarchical video exploration (the interactive schematic summaries). The VideoPerpetuoGram is extended and applied to different domains (video surveillance and snooker skill training), and an example of video visualization that solely depends on extracted features from video (the layered TimeRadarTrees) is discussed. Moreover, two sonification approaches with the purpose to improve situational awareness are introduced.