de.mpg.escidoc.pubman.appbase.FacesBean
English
 
Help Guide Disclaimer Contact us Login
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Evaluation of feature-based 3-d registration of probabilistic volumetric scenes

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons140746

Ulusoy,  A.O.
Dept. Perceiving Systems, Max Planck Institute for Intelligent Systems, Max Planck Society;

Locator

Link
(Any fulltext)

Fulltext (public)
There are no public fulltexts available
Supplementary Material (public)
There is no public supplementary material available
Citation

Restrepo, M. I., Ulusoy, A., & Mundy, J. L. (2014). Evaluation of feature-based 3-d registration of probabilistic volumetric scenes. ISPRS Journal of Photogrammetry and Remote Sensing, 98, 1-18. doi:10.1016/j.isprsjprs.2014.09.010.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0024-C4EA-3
Abstract
Automatic estimation of the world surfaces from aerial images has seen much attention and progress in recent years. Among current modeling technologies, probabilistic volumetric models (PVMs) have evolved as an alternative representation that can learn geometry and appearance in a dense and probabilistic manner. Recent progress, in terms of storage and speed, achieved in the area of volumetric modeling, opens the opportunity to develop new frameworks that make use of the \PVM\} to pursue the ultimate goal of creating an entire map of the earth, where one can reason about the semantics and dynamics of the 3-d world. Aligning 3-d models collected at different time-instances constitutes an important step for successful fusion of large spatio-temporal information. This paper evaluates how effectively probabilistic volumetric models can be aligned using robust feature-matching techniques, while considering different scenarios that reflect the kind of variability observed across aerial video collections from different time instances. More precisely, this work investigates variability in terms of discretization, resolution and sampling density, errors in the camera orientation, and changes in illumination and geographic characteristics. All results are given for large-scale, outdoor sites. In order to facilitate the comparison of the registration performance of \{PVMs\ to that of other 3-d reconstruction techniques, the registration pipeline is also carried out using Patch-based Multi-View Stereo (PMVS) algorithm. Registration performance is similar for scenes that have favorable geometry and the appearance characteristics necessary for high quality reconstruction. In scenes containing trees, such as a park, or many buildings, such as a city center, registration performance is significantly more accurate when using the PVM.