Mesh deformation-based single-view 3D reconstruction of thin eyeglasses frames with differentiable rendering

With the support of Virtual Reality (VR) and Augmented Reality (AR) technologies, the 3D virtual eyeglasses try-on application is well on its way to becoming a new trending solution that offers a “try on” option to select the perfect pair of eyeglasses at the comfort of your own home. Reconstructing eyeglasses frames from a single image with traditional depth and image-based methods is extremely difficult due to their unique characteristics such as lack of sufficient texture features, thin elements, and severe self-occlusions. In this paper, we propose the first mesh deformation-based reconstruction framework for recovering high-precision 3D full-frame eyeglasses models from a single RGB image, leveraging prior and domain-specific knowledge. Specifically, based on the construction of a synthetic eyeglasses frame dataset, we first define a class-specific eyeglasses frame template with pre-defined keypoints. Then, given an input eyeglasses frame image with thin structure and few texture features, we design a keypoint detector and refiner to detect predefined keypoints in a coarse-to-fine manner to estimate the camera pose accurately. After that, using differentiable rendering, we propose a novel optimization approach for producing correct geometry by progressively performing free-form deformation (FFD) on the template mesh. We define a series of loss functions to enforce consistency between the rendered result and the corresponding RGB input, utilizing constraints from inherent structure, silhouettes, keypoints, per-pixel shading information, and so on. Experimental results on both the synthetic dataset and real images demonstrate the effectiveness of the proposed algorithm. • A mesh deformation-based single-view reconstruction algorithm for thin eyeglasses. • A synthetic eyeglasses frame mesh dataset. • A coarse-to-fine network for detecting and refining keypoints. • An unsupervised free-form deformation method for refining reconstructed mesh.

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Publication Details

Journal
Graphical Models
Published
2024-08-09
DOI
https://doi.org/10.1016/j.gmod.2024.101225
Citations
2
Primary Topic
3D Shape Modeling and Analysis
Type
article
Field-Weighted Citation Impact
0.75
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article

Mesh deformation-based single-view 3D reconstruction of thin eyeglasses frames with differentiable rendering

Fan Zhang, Zhiyong Su, Weiqing Li, Ziyue Ji et al.
2 citations
Graphical Models
3D Shape Modeling and Analysis
0.75
article

Mesh deformation-based single-view 3D reconstruction of thin eyeglasses frames with differentiable rendering

Fan Zhang, Zhiyong Su, Weiqing Li, Ziyue Ji, Weiguang Kang
article en
2 citations

Abstract

With the support of Virtual Reality (VR) and Augmented Reality (AR) technologies, the 3D virtual eyeglasses try-on application is well on its way to becoming a new trending solution that offers a “try on” option to select the perfect pair of eyeglasses at the comfort of your own home. Reconstructing eyeglasses frames from a single image with traditional depth and image-based methods is extremely difficult due to their unique characteristics such as lack of sufficient texture features, thin elements, and severe self-occlusions. In this paper, we propose the first mesh deformation-based reconstruction framework for recovering high-precision 3D full-frame eyeglasses models from a single RGB image, leveraging prior and domain-specific knowledge. Specifically, based on the construction of a synthetic eyeglasses frame dataset, we first define a class-specific eyeglasses frame template with pre-defined keypoints. Then, given an input eyeglasses frame image with thin structure and few texture features, we design a keypoint detector and refiner to detect predefined keypoints in a coarse-to-fine manner to estimate the camera pose accurately. After that, using differentiable rendering, we propose a novel optimization approach for producing correct geometry by progressively performing free-form deformation (FFD) on the template mesh. We define a series of loss functions to enforce consistency between the rendered result and the corresponding RGB input, utilizing constraints from inherent structure, silhouettes, keypoints, per-pixel shading information, and so on. Experimental results on both the synthetic dataset and real images demonstrate the effectiveness of the proposed algorithm. • A mesh deformation-based single-view reconstruction algorithm for thin eyeglasses. • A synthetic eyeglasses frame mesh dataset. • A coarse-to-fine network for detecting and refining keypoints. • An unsupervised free-form deformation method for refining reconstructed mesh.

Graphical ModelsVol. 135
Nanjing University of Science and Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 34%
3D Shape Modeling and Analysis
0.75
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