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

Part of Advances in Neural Information Processing Systems 22 (NIPS 2009)

Bibtex Metadata Paper


Roy Anati, Kostas Daniilidis


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 are presented on four urban sequences and one indoor sequence.