Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud

Henrich P, Gyenes B, Scheikl P, Neumann G, Mathis-Ullrich F (2024)

Publication Language: English

Publication Type: Conference contribution

Publication year: 2024

Publisher: Institute of Electrical and Electronics Engineers Inc.

Pages Range: 3117-3126

Conference Proceedings Title: Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024

Event location: Waikoloa, HI US

ISBN: 9798350318920

DOI: 10.1109/WACV57701.2024.00310

Abstract

In deformable object manipulation, we often want to interact with specific segments of an object that are only defined in non-deformed models of the object. We thus require a system that can recognize and locate these segments in sensor data of deformed real world objects. This is normally done using deformable object registration, which is problem specific and complex to tune. Recent methods utilize neural occupancy functions to improve deformable object registration by registering to an object reconstruction. Going one step further, we propose a system that in addition to reconstruction learns segmentation of the reconstructed object. As the resulting output already contains the information about the segments, we can skip the registration process. Tested on a variety of deformable objects in simulation and the real world, we demonstrate that our method learns to robustly find these segments. We also introduce a simple sampling algorithm to generate better training data for occupancy learning.

Authors with CRIS profile

Pit Henrich Professur für Robotische Planung und Kognition in der Chirurgie Paul Scheikl Professur für Robotische Planung und Kognition in der Chirurgie Franziska Mathis-Ullrich Professur für Robotische Planung und Kognition in der Chirurgie

Involved external institutions

Karlsruhe Institute of Technology (KIT) DE Germany (DE)

How to cite

APA:

Henrich, P., Gyenes, B., Scheikl, P., Neumann, G., & Mathis-Ullrich, F. (2024). Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud. In Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024 (pp. 3117-3126). Waikoloa, HI, US: Institute of Electrical and Electronics Engineers Inc..

MLA:

Henrich, Pit, et al. "Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud." Proceedings of the 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024, Waikoloa, HI Institute of Electrical and Electronics Engineers Inc., 2024. 3117-3126.

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