Efficient object location determination and error analysis based on barycentric coordinates

Author:

Bodonyi Andrea,Kunkli RolandORCID

Abstract

AbstractIn this paper, we propose an efficient computational method for converting local coordinates to world coordinates using specially structured coordinate data. The problem in question is the computation of world coordinates of an object throughout a motion, assuming that we only know the changing coordinates of some fixed surrounding reference points in the local coordinate system of the object. The proposed method is based on barycentric coordinates; by taking the aforementioned static positions as the vertices of a polyhedron, we can specify the coordinates of the object in each step with the help of barycentric coordinates. This approach can significantly help us to achieve more accurate results than by using other possible methods. In the paper, we describe the problem and barycentric coordinate-based solution in detail. We then compare the barycentric method with a technique based on transformation matrices, which we also tested for solving our problem. We also present various diagrams that demonstrate the efficiency of our proposed approach in terms of precision and performance.

Publisher

Springer Science and Business Media LLC

Subject

Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Visual Arts and Performing Arts,Medicine (miscellaneous),Computer Science (miscellaneous),Software

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Joint Hand and Object Pose Estimation from a Single RGB Image using High‐level 2D Constraints;Computer Graphics Forum;2022-10

2. Label Guidance based Object Locating in Virtual Reality;2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR);2022-10

3. Features of hardware implementation of quasi-continuous observation devices with discrete receivers;Visual Computing for Industry, Biomedicine, and Art;2022-02-08

4. A barycentric coordinates-based visualization framework for movement of microscopic organisms;Annales Mathematicae et Informaticae;2021

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