Lane-Level Street Map Extraction From Aerial Imagery

Songtao He, Hari Balakrishnan; Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2022, pp. 2080-2089

Digital maps with lane-level details are the foundation of many applications. However, creating and maintaining digital maps especially maps with lane-level details, are labor-intensive and expensive. In this work, we propose a mapping pipeline to extract lane-level street maps from aerial imagery automatically. Our mapping pipeline first extracts lanes at non-intersection areas, then it enumerates all the possible turning lanes at intersections, validates the connectivity of them, and extracts the valid turning lanes to complete the map. We evaluate the accuracy of our mapping pipeline on a dataset consisting of four U.S. cities, demonstrating the effectiveness of our proposed mapping pipeline and the potential of scalable mapping solutions based on aerial imagery.