NDLI: Optimizing motion estimation with linear programming and detail-preserving variational method

Content Provider	IEEE Xplore Digital Library
Author	Hao Jiang Ze-Nian Li Drew, M.S.
Copyright Year	2004
Description	Author affiliation: Sch. of Comput. Sci., Simon Fraser Univ., Vancouver, BC, Canada (Hao Jiang; Ze-Nian Li; Drew, M.S.)
Abstract	We propose a novel linear programming based method to estimate arbitrary motion from two images. The proposed method always finds the global optimal solution of the linearized motion estimation energy function and thus is much more robust than traditional motion estimation schemes. As well, the method estimates the occlusion map and motion field at the same time. To further reduce the complexity of even a complexity-reduced pure linear programming method we present a two-phase scheme for estimating the dense motion field. In the first step, we estimate a relatively sparse motion field for the edge pixels using a non-regular sampling scheme, based on the proposed linear programming method In the second step, we set out a detail-preserving variational method to upgrade the result into a dense motion field. The proposed scheme is much faster than a purely linear programming based dense motion estimation scheme. And, since we use a global optimization method - linear programming - in the first estimation step, the proposed two-phase scheme is also significantly more robust than a pure variational scheme.
Sponsorship	IEEE Comput. Soc
File Size	941884
File Format	PDF
ISBN	0769521584
ISSN	10636919
DOI	10.1109/CVPR.2004.1315105
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-06-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimization methods Motion estimation Linear programming Image motion analysis Robustness Motion analysis Smoothing methods Sampling methods Object segmentation Object recognition
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Optical flow estimation on coarse-to-fine region-trees using discrete optimization

Local grouping for optical flow

Optimizing motion estimation with linear programming and detail-preserving variational method (2004)

Motion Detail Preserving Optical Flow Estimation

Optimizing motion estimation with linear programming and detail-preserving variational method (2004)

Motion detail preserving optical flow estimation

Optimizing Motion Estimation with Linear Programming and Detail-Preserving Variational Method (2004)

Image segmentation with simultaneous illumination and reflectance estimation: An energy minimization approach

A projective framework for scene segmentation in the presence of moving objects

Optimizing motion estimation with linear programming and detail-preserving variational method

Similar Documents

Optical flow estimation on coarse-to-fine region-trees using discrete optimization

Local grouping for optical flow

Optimizing motion estimation with linear programming and detail-preserving variational method (2004)

Motion Detail Preserving Optical Flow Estimation

Optimizing motion estimation with linear programming and detail-preserving variational method (2004)

Motion detail preserving optical flow estimation

Optimizing Motion Estimation with Linear Programming and Detail-Preserving Variational Method (2004)

Image segmentation with simultaneous illumination and reflectance estimation: An energy minimization approach

A projective framework for scene segmentation in the presence of moving objects

Optimizing motion estimation with linear programming and detail-preserving variational method