English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  NRSfM using Local Rigidity

Rehan, A., Zaheer, A., Akhter, I., Saeed, A., Mahmood, B., Usmani, M., et al. (2014). NRSfM using Local Rigidity. In Proceedings Winter Conference on Applications of Computer Vision (pp. 69-74). Steamboat Springs, CO, USA: IEEE. doi:10.1109/WACV.2014.6836116.

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Rehan, Ali1, Author
Zaheer, Aamer, Author
Akhter, Ijaz2, Author           
Saeed, Arfah, Author
Mahmood, Bilal, Author
Usmani, Muhammad, Author
Khan, Sohaib, Author
Affiliations:
1External Organizations, ou_persistent22              
2Dept. Perceiving Systems, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497642              

Content

show
hide
Free keywords: Abt. Black
 Abstract: Factorization methods for computation of nonrigid structure have limited practicality, and work well only when there is large enough camera motion between frames, with long sequences and limited or no occlusions. We show that typical nonrigid structure can often be approximated well as locally rigid sub-structures in time and space. Specifically, we assume that: 1) the structure can be approximated as rigid in a short local time window and 2) some point pairs stay relatively rigid in space, maintaining a fixed distance between them during the sequence. We first use the triangulation constraints in rigid SFM over a sliding time window to get an initial estimate of the nonrigid 3D structure. We then automatically identify relatively rigid point pairs in this structure, and use their length-constancy simultaneously with triangulation constraints to refine the structure estimate. Unlike factorization methods, the structure is estimated independent of the camera motion computation, adding to the simplicity and stability of the approach. Further, local factorization inherently handles significant natural occlusions gracefully, performing much better than the state-of-the art. We show more stable and accurate results as compared to the state-of-the art on even short sequences starting from 15 frames only, containing camera rotations as small as 2 degree and up to 50 percent missing data.

Details

show
hide
Language(s):
 Dates: 2014
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Rehan_wacv14
DOI: 10.1109/WACV.2014.6836116
 Degree: -

Event

show
hide
Title: IEEE Winter Conference on Applications of Computer Vision (WACV)
Place of Event: Steamboat Springs, CO
Start-/End Date: 2014-03-24 - 2014-03-26

Legal Case

show

Project information

show

Source 1

show
hide
Title: Proceedings Winter Conference on Applications of Computer Vision
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Steamboat Springs, CO, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 69 - 74 Identifier: -