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Human localization with fiber-optic sensors is a data-efficient, low-computational-cost substitute for vision-based approaches, especially, in indoor environments. A challenging task in building such a system is increasing the sensing efficiency, that is, the ratio of the number of monitored cells to that of sensors involved. In this paper, we develop a spatio-temporal Boolean compressed sensing model...
This paper concerns the issue of movement primitive extraction of handwriting, which is crucial to many applications with handwriting analysis. In particular, a novel analysis-by-synthesis paradigm is developed for extracting movement primitives from observed handwriting data. The logic behind our method is that complex human movements are the outcomes of the combinations of simple movement primitives...
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