NDLI: Self-Consistency and MDL: A Paradigm for Evaluating Point-Correspondence Algorithms, and Its Application to Detecting Changes in Surface Elevation

Content Provider	Springer Nature Link
Author	Leclerc, Yvan G. Luong, Q. Tuan Fua, P.
Copyright Year	2003
Abstract	The self-consistency methodology is a new paradigm for evaluating certain vision algorithms without relying extensively on ground truth. We demonstrate its effectiveness in the case of point-correspondence algorithms and use our approach to predict their accuracy.For point-correspondence algorithms, our methodology consists in applying independently the algorithm to subsets of images obtained by varying the camera geometry while keeping 3-D object geometry constant. Matches that should correspond to the same surface element in 3-D are collected to create statistics that are then used as a measure of the accuracy and reliability of the algorithm. These statistics can then be used to predict the accuracy and reliability of the algorithm applied to new images of new scenes.An effective representation for these statistics is a scatter diagram along two dimensions: A normalized distance and a matching score. The normalized distance make the statistics invariant to camera geometry, while the matching score allows us to predict the accuracy of individual matches. We introduce a new matching score based on Minimum Description Length (MDL) theory, which is shown to be a better predictor of the quality of a match than the traditional Sum of Squared Distance (SSD) score.We demonstrate the potential of our methodology in two different application areas. First, we compare different point-correspondence algorithms, matching scores, and window sizes. Second, we detect changes in terrain elevation between 3-D terrain models reconstructed from two sets of images taken at a different time.We finish by discussing the application of self-consistency to other vision problems.
Starting Page	63
Ending Page	83
Page Count	21
File Format	PDF
ISSN	09205691
Journal	International Journal of Computer Vision
Volume Number	51
Issue Number	1
e-ISSN	15731405
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2003-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Artificial Intelligence (incl. Robotics) Computer Imaging, Graphics and Computer Vision Image Processing Automation and Robotics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence 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

A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms

Recognition without Correspondence using Multidimensional Receptive Field Histograms

Self-Calibration of a Moving Camera from Point Correspondences and Fundamental Matrices

Shape and the Stereo Correspondence Problem

SoftPOSIT: Simultaneous Pose and Correspondence Determination

On the Geometry of Visual Correspondence

Rejecting Mismatches by Correspondence Function

Evaluation of Interest Point Detectors

On the Consistency of Instantaneous Rigid Motion Estimation

Self-Consistency and MDL: A Paradigm for Evaluating Point-Correspondence Algorithms, and Its Application to Detecting Changes in Surface Elevation

Similar Documents

A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms

Recognition without Correspondence using Multidimensional Receptive Field Histograms

Self-Calibration of a Moving Camera from Point Correspondences and Fundamental Matrices

Shape and the Stereo Correspondence Problem

SoftPOSIT: Simultaneous Pose and Correspondence Determination

On the Geometry of Visual Correspondence

Rejecting Mismatches by Correspondence Function

Evaluation of Interest Point Detectors

On the Consistency of Instantaneous Rigid Motion Estimation

Self-Consistency and MDL: A Paradigm for Evaluating Point-Correspondence Algorithms, and Its Application to Detecting Changes in Surface Elevation