NDLI: Segmentation and description based on perceptual organization

Content Provider	IEEE Xplore Digital Library
Author	Mohan, R. Nevatia, R.
Copyright Year	1989
Description	Author affiliation: Inst. for Robotics & Intelligent Syst., Univ. of Southern California, Los Angeles, CA, USA (Mohan, R.; Nevatia, R.)
Abstract	The authors present a description framework, motivated by perceptual organization, which consists of representations of the geometrical organizations of intensity discontinuities. The descriptors in this framework are called collated features, and are groupings identified by perceptual organization. The processes that operate on the image to obtain these descriptors and the visual processes that utilize them are discussed. The detection of collated features is robust to local problems. The structural information encoded in them aids various visual tasks such as object segmentation, correspondence processes (stereo, motion, and model matching), and shape inferences. Two primary grouping processes, cocurvilinearity and symmetry are applied to intensity edge contours to generate the collated features, including curves, symmetries, and ribbons. These collations can be used to segment into visible surfaces of objects and to describe the 2D shapes of those surfaces.<>
Starting Page	333
Ending Page	341
File Size	781897
Page Count	9
File Format	PDF
ISBN	081861952X
ISSN	10636919
DOI	10.1109/CVPR.1989.37869
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1989-06-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Layout Intelligent robots Visual perception Data mining Intelligent systems Computer vision Robustness Image segmentation Machine 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

Statistical recognition of motion patterns

Detection and description of buildings from multiple aerial images

Perceptual organization for scene segmentation and description

Inference of segmented, volumetric shape from three intensity images

Knowledge-based natural scene description

A new approach to machine-based perception of monocular images

Perception-based 3D triangle mesh segmentation using fast marching watersheds

Symmetry integrated region-based image segmentation

Recovering LSHGCs and SHGCs from stereo

Segmentation and description based on perceptual organization

Similar Documents

Statistical recognition of motion patterns

Detection and description of buildings from multiple aerial images

Perceptual organization for scene segmentation and description

Inference of segmented, volumetric shape from three intensity images

Knowledge-based natural scene description

A new approach to machine-based perception of monocular images

Perception-based 3D triangle mesh segmentation using fast marching watersheds

Symmetry integrated region-based image segmentation

Recovering LSHGCs and SHGCs from stereo

Segmentation and description based on perceptual organization