NDLI: A framework for uncertainty reasoning in hierarchical visual evidence space

Content Provider	IEEE Xplore Digital Library
Author	Qian, J. Ehrich, R.W.
Copyright Year	1990
Description	Author affiliation: Dept. of Electr. Eng. & Comput. Sci., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA (Qian, J.; Ehrich, R.W.)
Abstract	A computational framework is presented to show how Dempster-Shafer (D-S) evidence theory can be applied to a hierarchically structured hypothesis space in a computer vision system. It is shown how to make use of partial and locally ambiguous information at different levels of abstraction to achieve a reliable interpretation. It is also shown how the reasoning process can make use of spatial relationships among pieces of visual evidence to strengthen the reasoning results. Because a frame of discernment consists of a set of mutually exclusive visual events, the reasoning process is visual evidence driven, and the goal is to assign labels to visual events. However, at each level of the event hierarchy it is possible to pose additional D-S problems involving spatial relationships among hypotheses at that level and other evidence. The results of these subsidiary D-S problems contribute to the belief functions for the original hypotheses at that level. Thus, a framework for incorporating a relational model into an event-driven reasoning process is formed. An implementation example is given.
Starting Page	119
Ending Page	124
File Size	712985
Page Count	6
File Format	PDF
ISBN	0818620625
DOI	10.1109/ICPR.1990.118076
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1990-06-16
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Uncertainty Computer vision Feature extraction Machine vision Data mining Humans Artificial intelligence Data analysis Image analysis Degradation
Content Type	Text
Resource Type	Article

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

Evidence integration for 3D object recognition: a connectionist framework

Feature Mining for Image Classification

Feature extraction in human face recognition system

Feature-based Object Recognition

Mining visual complexity of images based on an enhanced feature space representation

A Framework for Visual Position Estimation for Motor Vehicles

Quotient Space Model Based Hierarchical Machine Learning

Applying uncertainty reasoning to model based object recognition

Gender Recognition in Non Controlled Environments

A framework for uncertainty reasoning in hierarchical visual evidence space

Similar Documents

Evidence integration for 3D object recognition: a connectionist framework

Feature Mining for Image Classification

Feature extraction in human face recognition system

Feature-based Object Recognition

Mining visual complexity of images based on an enhanced feature space representation

A Framework for Visual Position Estimation for Motor Vehicles

Quotient Space Model Based Hierarchical Machine Learning

Applying uncertainty reasoning to model based object recognition

Gender Recognition in Non Controlled Environments

A framework for uncertainty reasoning in hierarchical visual evidence space