eprintid: 8665
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/86/65
datestamp: 2023-11-09 16:20:35
lastmod: 2023-11-09 16:20:35
status_changed: 2023-11-09 16:13:13
type: conference_item
metadata_visibility: show
creators_name: Naffouti, S.E.
creators_name: Aouissaoui, I.
creators_name: Fougerolle, Y.
creators_name: Sakly, A.
creators_name: Meriaudeau, F.
title: Enhancement and assessment of WKS variance parameter for intelligent 3D shape recognition and matching based on MPSO
ispublished: pub
keywords: Particle swarm optimization (PSO), 3D shape recognition; Intelligent recognition; Kernel signatures; Modified particle swarm optimization; Modified particle swarm optimizations (MPSO); Shape matching; Shape recognition; Topological deformation, Robustness (control systems)
note: cited By 1; Conference of 4th International Conference on Control Engineering and Information Technology, CEIT 2016 ; Conference Date: 16 December 2016 Through 18 December 2016; Conference Code:127844
abstract: This paper presents an improved wave kernel signature (WKS) using the modified particle swarm optimization (MPSO)-based intelligent recognition and matching on 3D shapes. We select the first feature vector from WKS, which represents the 3D shape over the first energy scale. The choice of this vector is to reinforce robustness against non-rigid 3D shapes. Furthermore, an optimized WKS-based method for extracting key-points from objects is introduced. Due to its discriminative power, the associated optimized WKS values with each point remain extremely stable, which allows for efficient salient features extraction. To assert our method regarding its robustness against topological deformations, experiments show that the method is discriminative and robust to data perturbed by various noises. The algorithm is evaluated by its capability to differentiate between the salient feature points and to match efficiently between similar geometric structures for the same shape in different poses. © 2016 IEEE.
date: 2017
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020695824&doi=10.1109%2fCEIT.2016.7929021&partnerID=40&md5=b6564185cf6d333d835b87ebbfa711aa
id_number: 10.1109/CEIT.2016.7929021
full_text_status: none
publication: 4th International Conference on Control Engineering and Information Technology, CEIT 2016
refereed: TRUE
isbn: 9781509010554
citation:   Naffouti, S.E. and Aouissaoui, I. and Fougerolle, Y. and Sakly, A. and Meriaudeau, F.  (2017) Enhancement and assessment of WKS variance parameter for intelligent 3D shape recognition and matching based on MPSO.  In: UNSPECIFIED.