Body-relative navigation guidance using uncalibrated cameras

We present a vision-based method that assists human navigation within unfamiliar environments. Our main contribution is a novel algorithm that learns the correlation between user egomotion and feature matches on a wearable set of uncalibrated cameras. The primary advantage of this method is that it provides robust guidance cues in the user´s body frame, and is tolerant to small changes in the camera configuration. We couple this method with a topological mapping algorithm that provides global localization within the traversed environment. We validate our approach with ground-truth experiments and demonstrate the method on several real-world datasets spanning two kilometers of indoor and outdoor walking excursions.