Incremental texture mapping for autonomous driving

Miguel Oliveira, Vitor Santos, Angel D. Sappa, Paulo Dias, A. Paulo Moreira

    Research output: Contribution to journalArticleResearchpeer-review

    4 Citations (Scopus)


    © 2016 Elsevier B.V. Autonomous vehicles have a large number of on-board sensors, not only for providing coverage all around the vehicle, but also to ensure multi-modality in the observation of the scene. Because of this, it is not trivial to come up with a single, unique representation that feeds from the data given by all these sensors. We propose an algorithm which is capable of mapping texture collected from vision based sensors onto a geometric description of the scenario constructed from data provided by 3D sensors. The algorithm uses a constrained Delaunay triangulation to produce a mesh which is updated using a specially devised sequence of operations. These enforce a partial configuration of the mesh that avoids bad quality textures and ensures that there are no gaps in the texture. Results show that this algorithm is capable of producing fine quality textures.
    Original languageEnglish
    Pages (from-to)113-128
    JournalRobotics and Autonomous Systems
    Publication statusPublished - 1 Oct 2016


    • Autonomous driving
    • Scene reconstruction
    • Texture mapping


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