Constructing Topological Maps using Markov Random Fields and Loop-Closure Detection

We present a system which constructs a topological map of an environment given a sequence of images. This system includes a novel image similarity score which uses dynamic programming to match images using both the appearance and relative positions of local features simultaneously. Additionally, an MRF is constructed to model the probability of loop-closures. A locally optimal labeling is found using Loopy-BP. Finally we outline a method to generate a topological map from loop closure data. Results, presented on four urban sequences and one indoor sequence, outperform the state of the art.

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