TY  - JOUR
AU  - Miguel Oliveira
AU  - Victor Santos
AU  - Angel Sappa
AU  - P. Dias
AU  - A. Moreira
PY  - 2016//
TI  - Incremental texture mapping for autonomous driving
T2  - RAS
JO  - Robotics and Autonomous Systems
SP  - 113
EP  - 128
VL  - 84
KW  - Scene reconstruction
KW  - Autonomous driving
KW  - Texture mapping
N2  - 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.
UR  - https://doi.org/10.1016/j.robot.2016.06.009
L1  - http://refbase.cvc.uab.es/files/OSS2016b.pdf
N1  - ADAS; 600.086
ID  - Miguel Oliveira2016
ER  -