This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Search for Publication

Year(s) from:  to 
Keywords (separated by spaces):

Progressive Prioritized Multi-view Stereo

A. Locher, M. Perdoch and L. Van Gool
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
June 2016


This work proposes a progressive patch based multiview stereo algorithm able to deliver a dense point cloud at any time. This enables an immediate feedback on the reconstruction process in a user centric scenario. With increasing processing time, the model is improved in terms of resolution and accuracy. The algorithm explicitly handles input images with varying effective scale and creates visually pleasing point clouds. A priority scheme assures that the limited computational power is invested in scene parts, where the user is most interested in or the overall error can be reduced the most. The architecture of the proposed pipeline allows fast processing times in large scenes using a pure open-source CPU implementation. We show the performance of our algorithm on challenging standard datasets as well as on real-world scenes and compare it to the baseline.

Link to publisher's page
  author = {A. Locher and M. Perdoch and L. Van Gool},
  title = {Progressive Prioritized Multi-view Stereo},
  booktitle = {2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
  month = {June},
  pages = {3244-3252},
  keywords = {}