Model-based Pose Estimation for Texture-less Objects with Differential Evolution Algorithm

Model-based Pose Estimation for Texture-less Objects with Differential Evolution Algorithm

This paper proposes a novel object-tracking method to estimate three dimensions position of texture-less objects using one camera system and 3D model. The system uses efficient chamfer matching method to calculated distances between 2D edge templates of pose hypotheses with edges from the Canny edge...

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Bibliographic Details
Main Authors: Tao Linh, Nguyen Tinh, Hasegawa Hiroshi
Format: Article
Language:English
Published: EDP Sciences 2017-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201710815001
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spelling doaj-b61834f2bb424d29b628fe29629d01022021-02-02T02:35:40ZengEDP SciencesMATEC Web of Conferences2261-236X2017-01-011081500110.1051/matecconf/201710815001matecconf_icmaa2017_15001Model-based Pose Estimation for Texture-less Objects with Differential Evolution AlgorithmTao LinhNguyen TinhHasegawa HiroshiThis paper proposes a novel object-tracking method to estimate three dimensions position of texture-less objects using one camera system and 3D model. The system uses efficient chamfer matching method to calculated distances between 2D edge templates of pose hypotheses with edges from the Canny edge query image. Differential Evolution algorithm uses those distances as inputs to ensure the close optimum results and find the most suitable position of objects. For initialization the exhaustive searching is employed. With the good initialization, a smaller searching space is set to guaranty the online tracking ability. The first results showed the potential of the method in solving object tracking and detection problem.https://doi.org/10.1051/matecconf/201710815001
collection DOAJ
language English
format Article
sources DOAJ
author Tao Linh
Nguyen Tinh
Hasegawa Hiroshi
spellingShingle Tao Linh
Nguyen Tinh
Hasegawa Hiroshi
Model-based Pose Estimation for Texture-less Objects with Differential Evolution Algorithm
MATEC Web of Conferences
author_facet Tao Linh
Nguyen Tinh
Hasegawa Hiroshi
author_sort Tao Linh
title Model-based Pose Estimation for Texture-less Objects with Differential Evolution Algorithm
title_short Model-based Pose Estimation for Texture-less Objects with Differential Evolution Algorithm
title_full Model-based Pose Estimation for Texture-less Objects with Differential Evolution Algorithm
title_fullStr Model-based Pose Estimation for Texture-less Objects with Differential Evolution Algorithm
title_full_unstemmed Model-based Pose Estimation for Texture-less Objects with Differential Evolution Algorithm
title_sort model-based pose estimation for texture-less objects with differential evolution algorithm
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2017-01-01
description This paper proposes a novel object-tracking method to estimate three dimensions position of texture-less objects using one camera system and 3D model. The system uses efficient chamfer matching method to calculated distances between 2D edge templates of pose hypotheses with edges from the Canny edge query image. Differential Evolution algorithm uses those distances as inputs to ensure the close optimum results and find the most suitable position of objects. For initialization the exhaustive searching is employed. With the good initialization, a smaller searching space is set to guaranty the online tracking ability. The first results showed the potential of the method in solving object tracking and detection problem.
url https://doi.org/10.1051/matecconf/201710815001
work_keys_str_mv AT taolinh modelbasedposeestimationfortexturelessobjectswithdifferentialevolutionalgorithm
AT nguyentinh modelbasedposeestimationfortexturelessobjectswithdifferentialevolutionalgorithm
AT hasegawahiroshi modelbasedposeestimationfortexturelessobjectswithdifferentialevolutionalgorithm
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