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Coreset-Based Adaptive Tracking
[article]
2015
arXiv
pre-print
We propose a method for learning from streaming visual data using a compact, constant size representation of all the data that was seen until a given moment. Specifically, we construct a 'coreset' representation of streaming data using a parallelized algorithm, which is an approximation of a set with relation to the squared distances between this set and all other points in its ambient space. We learn an adaptive object appearance model from the coreset tree in constant time and logarithmic
arXiv:1511.06147v1
fatcat:zujkqnzvnjgytgarjfdanibhoa