276 research outputs found
Visual-assisted Outlier Preservation for Scatterplot Sampling
Scatterplot sampling has long been an efficient and effective way to resolve the overplotting issues commonly occurring in large-scale scatterplot visualization applications. However, it is challenging to preserve the existence of low-density points or outliers after sampling for a sub-sampling algorithm if, at the same time, faithfully representing the relative data densities is of importance. In this work, we propose to address this issue in a visual-assisted manner. While the whole dataset is sub-sampled, the density of the outliers is modeled and visually integrated into the final scatterplot together with the sub-sampled point data.
We showcase the effectiveness of our proposed method in various cases and user studies
Coach informed biomechanical analysis of the golf swing
Coach informed biomechanical analysis of the golf swin
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