NDLI: The combinatorics of heuristic search termination for object recognition in cluttered environments

Please wait, while we are loading the content...

The combinatorics of heuristic search termination for object recognition in cluttered environments

Content Provider	IEEE Xplore Digital Library
Author	Grimson, W.E.L.
Copyright Year	1979
Abstract	Many current recognition systems terminate a search once an interpretation that is good enough is found. The author formally examines the combinatorics of this approach, showing that choosing correct termination procedures can dramatically reduce the search. In particular, the author provides conditions on the object model and the scene clutter such that the expected search is at most quartic. The analytic results are shown to be in agreement with empirical data for cluttered object recognition. These results imply that it is critical to use techniques that select subsets of the data likely to have come from a single object before establishing a correspondence between data and model features.<>
Sponsorship	IEEE Computer Society
Starting Page	920
Ending Page	935
Page Count	16
File Size	1230687
File Format	PDF
ISSN	01628828
Volume Number	13
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1991-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Combinatorial mathematics Object recognition Sensor phenomena and characterization Layout Working environment noise Testing Search methods Performance analysis Computer science Contracts
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Computational Theory and Mathematics 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

The Combinatorics Of Object Recognition In Cluttered Environments Using Constrained Search

The effect of indexing on the complexity of object recognition

On the sensitivity of the Hough transform for object recognition

Automated concept acquisition in noisy environments

Using spin images for efficient object recognition in cluttered 3D scenes

On the verification of hypothesized matches in model-based recognition

A statistical-heuristic feature selection criterion for decision tree induction

Invariant descriptors for 3D object recognition and pose

Gaussian error models for object recognition

The combinatorics of heuristic search termination for object recognition in cluttered environments

Similar Documents

The Combinatorics Of Object Recognition In Cluttered Environments Using Constrained Search

The effect of indexing on the complexity of object recognition

On the sensitivity of the Hough transform for object recognition

Automated concept acquisition in noisy environments

Using spin images for efficient object recognition in cluttered 3D scenes

On the verification of hypothesized matches in model-based recognition

A statistical-heuristic feature selection criterion for decision tree induction

Invariant descriptors for 3D object recognition and pose

Gaussian error models for object recognition

The combinatorics of heuristic search termination for object recognition in cluttered environments