8 research outputs found

    Action-based multifield video visualization.

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    One challenge in video processing is to detect actions and events, known or unknown, in video streams dynamically. This paper proposes a visualization solution, where a video stream is depicted as a series of snapshots at a relatively sparse interval, and detected actions are highlighted with continuous abstract illustrations. The combined imagery and illustrative visualization conveys multi-field information in a manner similar to electrocardiograms (ECG) and seismographs. We thus name this type of video visualization as VideoPerpetuoGram (VPG). In this paper, we describe a system that handles the aw and processed information of the video stream in a multi-field visualization pipeline. As examples, we consider the needs for highlighting several types of processed information, including detected actions in video streams, and estimated relationship between recognized objects. We examine the effective means for depicting multi-field information in VPG, and support our choice of visual mappings through a survey. Our GPU implementation facilitates the VPG-specific viewing specification through a sheared object space, as well as volume bricking and combinational rendering of volume data and glyphs

    VizKid: A Behavior Capture and Visualization System of Adult-Child Interaction

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    Abstract. We present VizKid, a capture and visualization system for supporting the analysis of social interactions between two individuals. The development of this system is motivated by the need for objective measures of social approach and avoidance behaviors of children with autism. VizKid visualizes the position and orientation of an adult and a child as they interact with one another over an extended period of time. We report on the design of VizKid and its rationale

    Operation of HTS dc-SQUID sensors in high magnetic fields

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    Most visualization techniques have been designed on the assumption that the data to be represented are free from uncertainty. Yet this is rarely the case. Recently the visualization community has risen to the challenge of incorporating an indication of uncertainty into visual representations, and in this article we review their work. We place the work in the context of a reference model for data visualization, that sees data pass through a pipeline of processes. This allows us to distinguish the visualization of uncertainty - which considers how we depict uncertainty specified with the data - and the uncertainty of visualization - which considers how much inaccuracy occurs as we process data through the pipeline. It has taken some time for uncertain visualization methods to be developed, and we explore why uncertainty visualization is hard - one explanation is that we typically need to find another display dimension and we may have used these up already! To organise the material we return to a typology developed by one of us in the early days of visualization, and make use of this to present a catalogue of visualization techniques describing the research that has been done to extend each method to handle uncertainty. Finally we note the responsibility on us all to incorporate any known uncertainty into a visualization, so that integrity of the discipline is maintained
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