9 citations · 11 across the 3 of their papers we have counts for
5 papers
What makes visual place recognition easy or hard?
Stefan Schubert, Peer Neubert
Visual place recognition is a fundamental capability for the localization of mobile robots. It places image retrieval in the practical context of physical agents operating in a phy…
Beyond ANN: Exploiting Structural Knowledge for Efficient Place Recognition
Stefan Schubert, Peer Neubert, Peter Protzel
Visual place recognition is the task of recognizing same places of query images in a set of database images, despite potential condition changes due to time of day, weather or seas…
Hyperdimensional computing as a framework for systematic aggregation of image descriptors
Peer Neubert, Stefan Schubert
Image and video descriptors are an omnipresent tool in computer vision and its application fields like mobile robotics. Many hand-crafted and in particular learned image descriptor…
Graph-based non-linear least squares optimization for visual place recognition in changing environments
Stefan Schubert, Peer Neubert, Peter Protzel
Visual place recognition is an important subproblem of mobile robot localization. Since it is a special case of image retrieval, the basic source of information is the pairwise sim…
Unsupervised Learning Methods for Visual Place Recognition in Discretely and Continuously Changing Environments
Stefan Schubert, Peer Neubert, Peter Protzel
Visual place recognition in changing environments is the problem of finding matchings between two sets of observations, a query set and a reference set, despite severe appearance c…