A generic shape matching with anchoring of knowledge primitives of object ontology

Authors:
Dongil Han;Bum-Jae You;Yong Se Kim;Il Hong Suh
Affiliations:
Vision and Image Processing Lab., Sejong University, Seoul, Korea;Intelligent Robotics Research Center, Korea Institute of Science and Technology, Seoul, Korea;Creative Design and Intelligent Tutoring Systems Research Center, Sungkyunkwan University, Suwon, Korea;Intelligence and Interaction Lab., Hanyang University, Seoul, Korea
Venue:
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Year:
2005

Citing 5
Cited 1

Model-based recognition in robot vision

ACM Computing Surveys (CSUR)
Function-based generic recognition for multiple object categories

CVGIP: Image Understanding
Computer Vision: A Modern Approach

Computer Vision: A Modern Approach
RACER System Description

IJCAR '01 Proceedings of the First International Joint Conference on Automated Reasoning
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision

Fuzzy spatial relation ontology for image interpretation

Fuzzy Sets and Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

We have developed a generic ontology of objects, and a knowledge base of everyday physical objects. Objects are represented as assemblies of functional features and their spatial relations. Generic shape information of objects and features is stored using a partial boundary representation. Form-function reasoning is applied to deduce geometric shape elements from a feature's functions. We have also developed a generic geometric shape based object recognition method which uses many local features. The proposed recognition method considers the concept of ontology for representation of generic functions of objects. And the use of a general shape-function reasoning with context understanding enhances the performance of object recognition.