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.

Fontana, S., Sorrenti, D. (2021). A Termination Criterion for Probabilistic Point Clouds Registration. SIGNALS, 2(2), 159-173 [10.3390/signals2020013].

A Termination Criterion for Probabilistic Point Clouds Registration

Fontana S.
;
Sorrenti D. G.
2021

Abstract

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.
Articolo in rivista - Articolo scientifico
alignment; ICP; point cloud registration; point set;
English
2021
2
2
159
173
open
Fontana, S., Sorrenti, D. (2021). A Termination Criterion for Probabilistic Point Clouds Registration. SIGNALS, 2(2), 159-173 [10.3390/signals2020013].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/456007
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