Planar building facade segmentation and mapping using appearance and geometric constraints Conference Paper uri icon

abstract

  • © 2014 IEEE. Segmentation and mapping of planar building facades (PBFs) can increase a robot's ability of scene understanding and localization in urban environments which are often quasi-rectilinear and GPS-challenged. PBFs are basic components of the quasi-rectilinear environment. We propose a passive vision-based PBF segmentation and mapping algorithm by combining both appearance and geometric constraints. We propose a rectilinear index which allows us to segment out planar regions using appearance data. Then we combine geometric constraints such as reprojection errors, orientation constraints, and coplanarity constraints in an optimization process to improve the mapping of PBFs. We have implemented the algorithm and tested it in comparison with state-of-the-art. The results show that our method can reduce the angular error of scene structure by an average of 82.82%.

name of conference

  • 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014)

published proceedings

  • 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

author list (cited authors)

  • Lee, J., Lu, Y., & Song, D

citation count

  • 2

complete list of authors

  • Lee, Joseph||Lu, Yan||Song, Dezhen

publication date

  • September 2014

publisher