Abstract

We present a vision-based method that assists human navigation within unfamiliar environments. Our main contributionisanovelalgorithmthatlearnsthecorrelationbetween user egomotion and feature matches on a wearable setofuncalibratedcameras. Theprimaryadvantageofthis methodisthatitprovidesrobustguidancecuesintheuser’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. 1.Introductionand background Navigation is a fundamental task for humans that can

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