Hidden Markov model based graph matching for calibration of localization maps
S. Golnaz Shahidi, Shahrokh Valaee · 2015
We investigate the problem of graph matching to translate topological indoor localization to geographical localization, by modeling the building map and the semantic maps as graphs. A matching algorithm based on hidden Markov models is proposed. The matching algorithm is tested on both simulations and real data and accuracies as high as 94% on real data is achieved, while the matching is shown to be robust to noise, scale variance and partial matching via simulations.