From noisy point clouds to complete ear shapes: unsupervised pipeline

• URL: http://arxiv.org/abs/2008.09831v3
• Date: Fri, 4 Feb 2022 07:49:06 GMT
• Title: From noisy point clouds to complete ear shapes: unsupervised pipeline
• Authors: Filipa Valdeira, Ricardo Ferreira, Alessandra Micheletti, Cl\'audia Soares
• Abstract summary: We propose a complete pipeline taking as input unordered 3D point clouds with the aforementioned problems, and producing as output a dataset in correspondence. 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.
• Score: 63.8376359764052
• License: http://creativecommons.org/licenses/by/4.0/
• 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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