Matting and compositing of transparent and refractive objects

Author:

Yeung Sai-Kit1,Tang Chi-Keung2,Brown Michael S.3,Kang Sing Bing4

Affiliation:

1. University of California, Los Angeles

2. The Hong Kong University of Science and Technology, Hong Kong

3. National University of Singapore, Singapore

4. Microsoft Research Redmond, Redmond

Abstract

This article introduces a new approach for matting and compositing transparent and refractive objects in photographs. The key to our work is an image-based matting model, termed the Attenuation-Refraction Matte (ARM), that encodes plausible refractive properties of a transparent object along with its observed specularities and transmissive properties. We show that an object's ARM can be extracted directly from a photograph using simple user markup. Once extracted, the ARM is used to paste the object onto a new background with a variety of effects, including compound compositing, Fresnel effect, scene depth, and even caustic shadows. User studies find our results favorable to those obtained with Photoshop as well as perceptually valid in most cases. Our approach allows photo editing of transparent and refractive objects in a manner that produces realistic effects previously only possible via 3D models or environment matting.

Funder

Research Grants Council, University Grants Committee, Hong Kong

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design

Cited by 23 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Ray Deformation Networks for Novel View Synthesis of Refractive Objects;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

2. Semantic Image Matting: General and Specific Semantics;International Journal of Computer Vision;2023-10-12

3. TODE-Trans: Transparent Object Depth Estimation with Transformer;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

4. Eikonal Fields for Refractive Novel-View Synthesis;Special Interest Group on Computer Graphics and Interactive Techniques Conference Proceedings;2022-08-07

5. Semantic Image Matting;2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2021-06

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