Header logo is avg

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

2014

Conference Paper

ps


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.

Author(s): Restrepo, Maria I and Ulusoy, Ali O and Mundy, Joseph L
Book Title: ISPRS Journal of Photogrammetry and Remote Sensing
Volume: 98
Number (issue): 0
Pages: 1--18
Year: 2014

Department(s): Perceiving Systems
Bibtex Type: Conference Paper (inproceedings)
Paper Type: Journal

DOI: 10.1016/j.isprsjprs.2014.09.010

URL: http://www.sciencedirect.com/science/article/pii/S0924271614002354

Links: Publisher site

BibTex

@inproceedings{Restrepo20141,
  title = {{Evaluation of feature-based 3-d registration of probabilistic volumetric scenes}},
  author = {Restrepo, Maria I and Ulusoy, Ali O and Mundy, Joseph L},
  booktitle = {ISPRS Journal of Photogrammetry and Remote Sensing},
  volume = {98},
  number = {0},
  pages = {1--18},
  year = {2014},
  url = {http://www.sciencedirect.com/science/article/pii/S0924271614002354}
}