تقرير
Accurate Point Cloud Registration with Robust Optimal Transport
| العنوان: | Accurate Point Cloud Registration with Robust Optimal Transport |
|---|---|
| المؤلفون: | Shen, Zhengyang, Feydy, Jean, Liu, Peirong, Curiale, Ariel Hernán, Estepar, Ruben San Jose, Estepar, Raul San Jose, Niethammer, Marc |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Computational Geometry, I.2.10 |
| الوصف: | This work investigates the use of robust optimal transport (OT) for shape matching. Specifically, we show that recent OT solvers improve both optimization-based and deep learning methods for point cloud registration, boosting accuracy at an affordable computational cost. This manuscript starts with a practical overview of modern OT theory. We then provide solutions to the main difficulties in using this framework for shape matching. Finally, we showcase the performance of transport-enhanced registration models on a wide range of challenging tasks: rigid registration for partial shapes; scene flow estimation on the Kitti dataset; and nonparametric registration of lung vascular trees between inspiration and expiration. Our OT-based methods achieve state-of-the-art results on Kitti and for the challenging lung registration task, both in terms of accuracy and scalability. We also release PVT1010, a new public dataset of 1,010 pairs of lung vascular trees with densely sampled points. This dataset provides a challenging use case for point cloud registration algorithms with highly complex shapes and deformations. Our work demonstrates that robust OT enables fast pre-alignment and fine-tuning for a wide range of registration models, thereby providing a new key method for the computer vision toolbox. Our code and dataset are available online at: https://github.com/uncbiag/robot. Comment: Accepted in NeurIPS 2021 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2111.00648 |
| رقم الأكسشن: | edsarx.2111.00648 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |