NDLI: 3-D object pose estimation by shading and edge data fusion-simulating virtual manipulation on mental images

Content Provider	IEEE Xplore Digital Library
Author	Nomura, Y. Dili Zhang Sakaida, Y. Fujii, S.
Copyright Year	1996
Description	Author affiliation: Sch. of Eng., Nagoya Univ., Japan (Nomura, Y.; Dili Zhang; Sakaida, Y.; Fujii, S.)
Abstract	Human beings seem to recognize objects based on a kind of model-matching, i.e., a virtual manipulation on mental images. This paper presents a 3-D object pose estimation method simulating the human recognition scheme. Computer synthesizes not only an edge image but also a shading image from an object model. Then, it matches the two kinds of synthesized images with the inputted images individually by using a non-linear least-squares method, and estimates the pose parameter values. Finally, it chooses the better of the individually estimated poses. Thus, the fusion of the shading and the edge information is achieved. Since the two pieces of information complement each other, this method has the advantage of much higher robustness and accuracy of pose estimation than ordinary model-matching techniques which rely only on geometrical features such as vertices or edges.
Starting Page	866
Ending Page	871
File Size	583291
Page Count	6
File Format	PDF
ISBN	0818672595
ISSN	10636919
DOI	10.1109/CVPR.1996.517173
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	Image matching Humans Image recognition Object recognition Image segmentation Solid modeling Surface reconstruction Shape Cameras Computer vision
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

3-D object pose estimation based on iterative image matching: Shading and edge data fusion

Variable albedo surface reconstruction from stereo and shape from shading

Shape from video

Automatic line matching across views

Better Shading for Better Shape Recovery

Shape from symmetry

From contours to 3D object detection and pose estimation

Symmetric piecewise planar object reconstruction from a single image

Using silhouette for pose estimation of object with surface of revolution

3-D object pose estimation by shading and edge data fusion-simulating virtual manipulation on mental images

Similar Documents

3-D object pose estimation based on iterative image matching: Shading and edge data fusion

Variable albedo surface reconstruction from stereo and shape from shading

Shape from video

Automatic line matching across views

Better Shading for Better Shape Recovery

Shape from symmetry

From contours to 3D object detection and pose estimation

Symmetric piecewise planar object reconstruction from a single image

Using silhouette for pose estimation of object with surface of revolution

3-D object pose estimation by shading and edge data fusion-simulating virtual manipulation on mental images