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
Cited by
5 articles.
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