PIRF 3D: Online spatial and appearance based loop closure

In this paper, an online spatial and appearance based loop closure algorithm is presented. The approach is based on a graph matching formulation using Position Invariant Robust Features (PIRF), extending previous approaches based on PIRF by incorporating spatial information. The vertices of the graph represent visual words/features and edges represent metric information with uncertainty since the spatial distances observed between visual words are prone to errors. This method is capable of detecting loop closure in urban environments based on visual appearance as well as spatial layout of matched visual features. A vocabulary is built in an online and incremental manner, also storing spatial distances between visual words. The algorithm is capable of assigning loop closure with higher confidence values and a higher recall rate while maintaining precision compared to approaches where only visual appearance methods are used. We evaluate this approach on a publicly available dataset and present experimental results.