Line and Plane based Incremental Surface Reconstruction

• Author / Creator

  Ahmad, Junaid

• Simultaneous Localization and Mapping(SLAM) has been very popular in the
  past and is gaining more traction in the era of autonomous vehicle research
  and robot manipulation. Computing accurate surface models from sparse Visual SLAM 3D point clouds is difcult. There have been works where this
  problem was addressed by space carving methods using map points and lines
  generated by those points. These methods come with their own drawbacks
  as point clouds and lines alone don’t add sufcient structural information to
  the scene. In this thesis, we try to take the natural step to also compute
  and verify 3D planes bottom-up from lines. Our system takes the real-time
  stream of new cameras and 3D points from a SLAM system and incrementally
  builds the 3D scene surface model. In previous work, 3D line segments were
  detected in relevant keyframes and were fed to the modeling algorithm for
  surface reconstruction. This method has an immediate drawback as some of
  the line segments generated in every keyframe are redundant and mark similar objects(shifted) creating clutter in the map. To avoid this issue, we track
  the 3D planes detected over keyframes for consistency and data association.
  Furthermore, the smoother and better-aligned model surfaces result in more
  photo-realistic rendering using keyframe texture images. Compared to other
  incremental real-time surface reconstruction methods, our model has less than
  half the triangles, and we achieve better metric reconstruction accuracy on the
  EuRoC MAV Benchmarks. We also tested our method on various of-the-shelf
  cameras for better generalization

• Subjects / Keywords

  • Computer Vision
  • 3D Reconstruction
  • SLAM
  • Incremental

• Graduation date

  Spring 2023

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-x996-2z18

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.