Full 3D Reconstruction of Non-Rigidly Deforming Objects

Author:

Afzal Hassan1,Aouada Djamila1,Mirbach Bruno2,Ottersten Björn1

Affiliation:

1. University of Luxembourg, Luxembourg

2. IEE S.A., Luxembourg

Abstract

In this article, we discuss enhanced full 360° 3D reconstruction of dynamic scenes containing non-rigidly deforming objects using data acquired from commodity depth or 3D cameras. Several approaches for enhanced and full 3D reconstruction of non-rigid objects have been proposed in the literature. These approaches suffer from several limitations due to requirement of a template, inability to tackle large local deformations and topology changes, inability to tackle highly noisy and low-resolution data, and inability to produce online results. We target online and template-free enhancement of the quality of noisy and low-resolution full 3D reconstructions of dynamic non-rigid objects. For this purpose, we propose a view-independent recursive and dynamic multi-frame 3D super-resolution scheme for noise removal and resolution enhancement of 3D measurements. The proposed scheme tracks the position and motion of each 3D point at every timestep by making use of the current acquisition and the result of the previous iteration. The effects of system blur due to per-point tracking are subsequently tackled by introducing a novel and efficient multi-level 3D bilateral total variation regularization. These characteristics enable the proposed scheme to handle large deformations and topology changes accurately. A thorough evaluation of the proposed scheme on both real and simulated data is carried out. The results show that the proposed scheme improves upon the performance of the state-of-the-art methods and is able to accurately enhance the quality of low-resolution and highly noisy 3D reconstructions while being robust to large local deformations.

Funder

Fonds National de la Recherche (FNR), Luxembourg

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture

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1. Geometric and Learning-Based Mesh Denoising: A Comprehensive Survey;ACM Transactions on Multimedia Computing, Communications, and Applications;2023-11-10

2. Contrastive Attention-guided Multi-level Feature Registration for Reference-based Super-resolution;ACM Transactions on Multimedia Computing, Communications, and Applications;2023-10-18

3. Sequential Hierarchical Learning with Distribution Transformation for Image Super-Resolution;ACM Transactions on Multimedia Computing, Communications, and Applications;2023-01-23

4. A Spatial Relationship Preserving Adversarial Network for 3D Reconstruction from a Single Depth View;ACM Transactions on Multimedia Computing, Communications, and Applications;2022-03-04

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