A Termination Criterion for Probabilistic Point Clouds Registration
Probabilistic Point Clouds Registration (PPCR) is an algorithm that, in its multi-iteration version, outperformed state-of-the-art algorithms for local point clouds registration. However, its performances have been tested using a fixed high number of iterations. To be of practical usefulness, we thi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Signals |
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| Online Access: | https://www.mdpi.com/2624-6120/2/2/13 |
| _version_ | 1797540248528355328 |
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| author | Simone Fontana Domenico Giorgio Sorrenti |
| author_facet | Simone Fontana Domenico Giorgio Sorrenti |
| author_sort | Simone Fontana |
| collection | DOAJ |
| description | Probabilistic Point Clouds Registration (PPCR) is an algorithm that, in its multi-iteration version, outperformed state-of-the-art algorithms for local point clouds registration. However, its performances have been tested using a fixed high number of iterations. To be of practical usefulness, we think that the algorithm should decide by itself when to stop, on one hand to avoid an excessive number of iterations and waste computational time, on the other to avoid getting a sub-optimal registration. With this work, we compare different termination criteria on several datasets, and prove that the chosen one produces very good results that are comparable to those obtained using a very large number of iterations, while saving computational time. |
| first_indexed | 2024-03-10T12:58:24Z |
| format | Article |
| id | doaj.art-bec8f10393d54f479ab9d4cb5380fe7b |
| institution | Directory Open Access Journal |
| issn | 2624-6120 |
| language | English |
| last_indexed | 2024-03-10T12:58:24Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Signals |
| spelling | doaj.art-bec8f10393d54f479ab9d4cb5380fe7b2023-11-21T11:45:13ZengMDPI AGSignals2624-61202021-03-012215917310.3390/signals2020013A Termination Criterion for Probabilistic Point Clouds RegistrationSimone Fontana0Domenico Giorgio Sorrenti1Department of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca, 20126 Milano, ItalyDepartment of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca, 20126 Milano, ItalyProbabilistic Point Clouds Registration (PPCR) is an algorithm that, in its multi-iteration version, outperformed state-of-the-art algorithms for local point clouds registration. However, its performances have been tested using a fixed high number of iterations. To be of practical usefulness, we think that the algorithm should decide by itself when to stop, on one hand to avoid an excessive number of iterations and waste computational time, on the other to avoid getting a sub-optimal registration. With this work, we compare different termination criteria on several datasets, and prove that the chosen one produces very good results that are comparable to those obtained using a very large number of iterations, while saving computational time.https://www.mdpi.com/2624-6120/2/2/13point cloud registrationpoint setICPalignment |
| spellingShingle | Simone Fontana Domenico Giorgio Sorrenti A Termination Criterion for Probabilistic Point Clouds Registration Signals point cloud registration point set ICP alignment |
| title | A Termination Criterion for Probabilistic Point Clouds Registration |
| title_full | A Termination Criterion for Probabilistic Point Clouds Registration |
| title_fullStr | A Termination Criterion for Probabilistic Point Clouds Registration |
| title_full_unstemmed | A Termination Criterion for Probabilistic Point Clouds Registration |
| title_short | A Termination Criterion for Probabilistic Point Clouds Registration |
| title_sort | termination criterion for probabilistic point clouds registration |
| topic | point cloud registration point set ICP alignment |
| url | https://www.mdpi.com/2624-6120/2/2/13 |
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