NDLI: Finding corresponding points based on Bayesian triangulation

Content Provider	IEEE Xplore Digital Library
Author	Bedekar, A.S. Haralick, R.M.
Copyright Year	1996
Description	Author affiliation: Dept. of Electr. Eng., Washington Univ., Seattle, WA, USA (Bedekar, A.S.; Haralick, R.M.)
Abstract	In this paper, we consider the problems of finding corresponding points from multiple perspective projection images (the correspondence problem), and estimating the 3-D point from which these points have arisen (the triangulation problem). We pose the triangulation problem as that of finding the Bayesian maximum, a posteriori estimate of the 3-D point, given its projections in N images, assuming a Gaussian error model for the image point co-ordinates and the camera parameters. We solve this by an iterative steepest descent method. We then consider the correspondence problem as a, statistical hypothesis verification problem. Given a set of 2-D points, under the hypothesis that the points are in correspondence, the MAP estimate of the 3-D point is computed. Based on the MAP estimate, we derive a statistical test for verifying this hypothesis. To find sets of corresponding points when multiple points in each of N images are given, we propose a method that does the Bayesian triangulation and hypothesis verification on each N-tuple of points, selecting those that pass the hypothesis test. We characterize the performance of the Bayesian triangulation in terms of the average distance of the triangulated 3-D point from the true 3-D point, and of the point correspondence method in terms of its misdetection and false alarm rates.
Starting Page	61
Ending Page	66
File Size	614617
Page Count	6
File Format	PDF
ISBN	0818672595
ISSN	10636919
DOI	10.1109/CVPR.1996.517054
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-06-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian methods Cameras Testing Gaussian processes Iterative methods Layout Object recognition Image analysis Gaussian noise
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

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