Motivated by the problems of vision-based mobile robot map building and localization, we present a comparative study of statistical methods for matching image features in a wide base line between learning and recognition phases. A general methodology called feature-class method for the problem of fast matching image features in a wide base line is described in the context of mobile robots. The objective of this work is to discuss and to show the performance of such methods in an example of visual SLAM, with experiments done with real data.

Peer Reviewed