Global Heading Estimation for Wide Area Augmented Reality Using Road Semantics for Geo-referencing

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Citation

T. Oskiper, S. Samarasekera and R. Kumar, “Global Heading Estimation For Wide Area Augmented Reality Using Road Semantics For Geo-referencing,” 2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), 2021, pp. 427-428, doi: 10.1109/ISMAR-Adjunct54149.2021.00096.

Abstract

In this paper, we present a method to estimate global camera heading by associating directional information from road segments in the camera view with annotated satellite imagery. The system is based on a multi-sensor fusion framework that relies on GPS, camera and an inertial measurement unit (IMU). The backbone of the system is built on a very strong visual-inertial navigation (VIO) pipeline with very low drift rate and the proposed algorithm combines relative motion provided by VIO with global cues obtained by an image segmentation module to extract heading information for geo-referenced AR applications over wide area.

Keywords: Image segmentation, Visualization, Satellites, Measurement units, Head, Roads, Semantics.

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