Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

PatchFusion: Patch-based Nonrigid Tracking and Reconstruction of Deformable Objects using a Single RGB-D Sensor

Version 1 : Received: 26 March 2024 / Approved: 27 March 2024 / Online: 27 March 2024 (14:11:39 CET)

How to cite: Zhao, M.; Yu, X.; Xu, L. PatchFusion: Patch-based Nonrigid Tracking and Reconstruction of Deformable Objects using a Single RGB-D Sensor. Preprints 2024, 2024031670. https://doi.org/10.20944/preprints202403.1670.v1 Zhao, M.; Yu, X.; Xu, L. PatchFusion: Patch-based Nonrigid Tracking and Reconstruction of Deformable Objects using a Single RGB-D Sensor. Preprints 2024, 2024031670. https://doi.org/10.20944/preprints202403.1670.v1

Abstract

This paper introduces PatchFusion, an innovative approach for nonrigid tracking and reconstruction of deformable objects using a single RGB-D sensor. Existing methods face challenges in accurately capturing the rapid deformations of soft and flexible objects, thereby limiting their utility in diverse scenarios. Our approach overcomes this challenge by employing a dynamic patch-based framework that adapts to rapid inter-frame motions. Firstly, patch-wise rigid transformation fields for non-overlapping patches are solved via Iterative Closest Point (ICP) by incorporating geometric features as additional similarity constraints, thereby enhancing robustness and accuracy. Secondly, deformation optimization based on a nonrigid solver is applied to refine the coarse transformation fields. In order to enable simultaneous tracking and reconstruction of deformable objects, the patch-based rigid solver is designed to run in parallel with the nonrigid solver, serving as a plug-and-play module requiring minimal modifications for integration while enabling real-time performance. Following a comprehensive evaluation, PatchFusion showcases superior performance in effectively dealing with rapid inter-frame deformations when compared to existing techniques, rendering it a promising solution with broad applicability across domains such as robotics, computer vision, and human-computer interaction.

Keywords

nonrigid tracking; deformable objects; RGB-D sensor; deformation optimization

Subject

Computer Science and Mathematics, Computer Vision and Graphics

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