Sublinear Subwindow Search
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We propose an efficient approximation algorithm for subwindow search that runs in sublinear time and memory. Applied to object localization, this algorithm significantly reduces running time and memory usage while maintaining competitive accuracy scores compared to the state-of-the-art. The algorithm's accuracy also scales with both the size and the spatial coherence (nearby-element similarity) of the matrix. It is thus well-suited for real-time applications and against many matrices in general.
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