title: Part-based object retrieval in cluttered environment.
abstract: A novel local structural approach, which is a sequel to our previous work, is proposed in this paper for object retrieval in a cluttered and occluded environment without identifying the outlines of an object. It works by first extracting consistent and structurally unique local neighborhood from inputs or models and then voting on the optimal matches employing dynamic programming and a novel hypercube-based indexing structure. The proposed concepts have been tested on a database with thousands of images and compared with the six nearest-neighbors shape description with superior results.
authors.affiliation: School of Computer Engineering, Nanyang Technological University, Singapore. chiyanling@pmail.ntu.edu.sg
authors.forename: Yanling
authors.initials: Y
authors.lastname: Chi
authors.forename: Maylor K H
authors.initials: MK
authors.lastname: Leung
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*