Fast and robust motion averaging via angle constraints of multi‐view range scans
Abstract The motion averaging problem arises when recovering the motions for a set of scans in three‐dimensional (3D) reconstruction. Motion averaging is taken as an optimisation problem, whose solution can be obtained via matrix decomposition in principal component analysis. The latest motion avera...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-02-01
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| Series: | The Journal of Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/tje2.12014 |
| _version_ | 1811261305477136384 |
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| author | Xin Zhang Yan Zhang Chengzhi Qu Zhuangbin Tan |
| author_facet | Xin Zhang Yan Zhang Chengzhi Qu Zhuangbin Tan |
| author_sort | Xin Zhang |
| collection | DOAJ |
| description | Abstract The motion averaging problem arises when recovering the motions for a set of scans in three‐dimensional (3D) reconstruction. Motion averaging is taken as an optimisation problem, whose solution can be obtained via matrix decomposition in principal component analysis. The latest motion averaging methods utilize the Cauchy kernel function or overlap rate to construct the weighted matrix in the cost function, yielding weighted low‐rank sparse matrix decomposition solutions. Nevertheless, the over‐reliance on the initial value and high computational complexity remain two major problems. Here, we aim to improve the motion averaging performance via a fast and robust method based on the angle constraints of multiple scans. The additional term representing the angle constraint is added into the original cost function. By doing this, two benefits are facilitated: 1) the iteration times for the optimisation process are reduced; and 2) it effectively mitigates the over‐reliance on the initial value and thus caters for outliers and random noise of initial motions. Compared with state‐of‐the‐art motion averaging methods, it is indicated that the proposed method is more efficient and robust for numerical simulations of using both simulated motions and real 3D scanning data, given a large range of angle constraint values. |
| first_indexed | 2024-04-12T19:02:17Z |
| format | Article |
| id | doaj.art-8a527003f0b548ea8a27d44efcbd1b3d |
| institution | Directory Open Access Journal |
| issn | 2051-3305 |
| language | English |
| last_indexed | 2024-04-12T19:02:17Z |
| publishDate | 2021-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Journal of Engineering |
| spelling | doaj.art-8a527003f0b548ea8a27d44efcbd1b3d2022-12-22T03:20:07ZengWileyThe Journal of Engineering2051-33052021-02-012021210411310.1049/tje2.12014Fast and robust motion averaging via angle constraints of multi‐view range scansXin Zhang0Yan Zhang1Chengzhi Qu2Zhuangbin Tan3School of Aeronautics and Astronautics Sun Yat‐sen University, Shenzhen Campus Gongchang road, Shenzhen, China Shenzhen 518106 ChinaSchool of Aeronautics and Astronautics Sun Yat‐sen University, Shenzhen Campus Gongchang road, Shenzhen, China Shenzhen 518106 ChinaSchool of Aeronautics and Astronautics Sun Yat‐sen University, Shenzhen Campus Gongchang road, Shenzhen, China Shenzhen 518106 ChinaSchool of Aeronautics and Astronautics Sun Yat‐sen University, Shenzhen Campus Gongchang road, Shenzhen, China Shenzhen 518106 ChinaAbstract The motion averaging problem arises when recovering the motions for a set of scans in three‐dimensional (3D) reconstruction. Motion averaging is taken as an optimisation problem, whose solution can be obtained via matrix decomposition in principal component analysis. The latest motion averaging methods utilize the Cauchy kernel function or overlap rate to construct the weighted matrix in the cost function, yielding weighted low‐rank sparse matrix decomposition solutions. Nevertheless, the over‐reliance on the initial value and high computational complexity remain two major problems. Here, we aim to improve the motion averaging performance via a fast and robust method based on the angle constraints of multiple scans. The additional term representing the angle constraint is added into the original cost function. By doing this, two benefits are facilitated: 1) the iteration times for the optimisation process are reduced; and 2) it effectively mitigates the over‐reliance on the initial value and thus caters for outliers and random noise of initial motions. Compared with state‐of‐the‐art motion averaging methods, it is indicated that the proposed method is more efficient and robust for numerical simulations of using both simulated motions and real 3D scanning data, given a large range of angle constraint values.https://doi.org/10.1049/tje2.12014AlgebraOptimisation techniquesInterpolation and function approximation (numerical analysis)Optical, image and video signal processingAlgebraOptimisation techniques |
| spellingShingle | Xin Zhang Yan Zhang Chengzhi Qu Zhuangbin Tan Fast and robust motion averaging via angle constraints of multi‐view range scans The Journal of Engineering Algebra Optimisation techniques Interpolation and function approximation (numerical analysis) Optical, image and video signal processing Algebra Optimisation techniques |
| title | Fast and robust motion averaging via angle constraints of multi‐view range scans |
| title_full | Fast and robust motion averaging via angle constraints of multi‐view range scans |
| title_fullStr | Fast and robust motion averaging via angle constraints of multi‐view range scans |
| title_full_unstemmed | Fast and robust motion averaging via angle constraints of multi‐view range scans |
| title_short | Fast and robust motion averaging via angle constraints of multi‐view range scans |
| title_sort | fast and robust motion averaging via angle constraints of multi view range scans |
| topic | Algebra Optimisation techniques Interpolation and function approximation (numerical analysis) Optical, image and video signal processing Algebra Optimisation techniques |
| url | https://doi.org/10.1049/tje2.12014 |
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