Vision Global Localization with Semantic Segmentation and Interest Feature Points
Kai Li,Xudong Zhang,Kun LI,Shuo Zhang,Kai Li,Xudong Zhang,Kun LI,Shuo Zhang
In this work, we present a vision-only global localization architecture for autonomous vehicle applications, and achieves centimeter-level accuracy and high robustness in various scenarios. We first apply pixel-wise segmentation to the front-view mono camera and extract the semantic features, e.g. pole-like objects, lane markings, and curbs, which are robust to illumination, viewing angles and sea...
