Visual localization and loop closing using decision trees and binary features

In this paper we present an approach for efficiently retrieving the most similar image, based on point-to-point correspondences, within a sequence that has been acquired through continuous camera movement. Our approach is entailed to the use of standardized binary feature descriptors and exploits the temporal form of the input data to dynamically adapt the search structure. While being straightforward to implement, our method exhibits very fast response times and its Precision/Recall rates compete with state of the art approaches. Our claims are supported by multiple large scale experiments on publicly available datasets.