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This paper proposes spatiotemporal volume saliency to detect and explore salient regions in time-varying volume data. Based on the center-surround hypothesis that the salient region stands out from its surroundings, we extend the spatial saliency to time domain and introduce temporal volume saliency. It is defined as a center-surround operator on Gaussian-weighted mean attribute gradient between steps...
Interactive visualization has become a valuable tool in visual exploration of scientific data. One prerequisite and fundamental issue is how to infer three-dimensional information through users’ two-dimensional input. Existing approaches commonly build on the hypothesis that user input is precise, which is sometimes invalid because of multiple causes like data noise, limited resolution of display...
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