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arXiv · 2008.09831

From noisy point clouds to complete ear shapes: unsupervised pipeline

Filipa Valdeira·Ricardo Ferreira·Alessandra Micheletti·Cláudia Soares
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Abstract

Ears are a particularly difficult region of the human face to model, not only due to the non-rigid deformations existing between shapes but also to the challenges in processing the retrieved data. The first step towards obtaining a good model is to have complete scans in correspondence, but these usually present a higher amount of occlusions, noise and outliers when compared to most face regions, thus requiring a specific procedure. Therefore, we propose a complete pipeline taking as input unordered 3D point clouds with the aforementioned problems, and producing as output a dataset in correspondence, with completion of the missing data. We provide a comparison of several state-of-the-art registration methods and propose a new approach for one of the steps of the pipeline, with better performance for our data.

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Filipa Valdeira, Ricardo Ferreira, Alessandra Micheletti, Cláudia Soares. 2020-08-22. From noisy point clouds to complete ear shapes: unsupervised pipeline. https://doi.org/10.1109/access.2021.3111811

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