文章基本信息

标题：Model-based Pose Estimation for Texture-less Objects with Differential Evolution Algorithm
本地全文：下载
作者：Linh Tao ; Linh Tao ; Tinh Nguyen 等
期刊名称：MATEC Web of Conferences
电子版ISSN：2261-236X
出版年度：2017
卷号：108
页码：1-4
DOI：10.1051/matecconf/201710815001
语种：English
出版社：EDP Sciences
摘要：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.