Sublinear Subwindow Search.
Year: 2019
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Max Reuter, Gheorghe-Teodor Bercea
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2964959081