research-article

QuickCSGModeling: Quick CSG Operations Based on Fusing Signed Distance Fields for VR Modeling

Authors:

Shuangmin Chen,

Lin LuAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications and Applications, Volume 20, Issue 7

Article No.: 189, Pages 1 - 18

https://doi.org/10.1145/3599729

Published: 27 March 2024 Publication History

Abstract

The latest advancements in Virtual Reality (VR) enable the creation of 3D models within a holographic immersive simulation environment. In this article, we create QuickCSGModeling, a user-friendly mid-air interactive modeling system. We first prepare a dataset consisting of diverse components and precompute the discrete signed distance function (SDF) for each component. During the modeling phase, users can freely design complicated shapes with a pair of VR controllers. Based on the discrete SDF representation, any CSG-like operation (union, intersection, and subtraction) can be performed voxel-wisely. Also, we maintain a single dynamic SDF for the whole scene, whose zero-level set surface exactly encodes the most recent constructed shape. Both SDF fusion and surface extraction are implemented via GPU for a smooth user experience. A total of 34 volunteers were asked to create their favorite models using QuickCSGModeling. With a simple training, most of them can create a fascinating shape or even a descriptive scene quickly. We also discuss how to extend our system to create articulated models with hinges, where an adaptive cube subdivision has to be enforced to improve the reconstruction accuracy around the hinge part, followed by a Dual Contouring-based surface extraction.

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Cited By

Wen HSong XChen XWei YNie LChua THui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Simple but Effective Raw-Data Level Multimodal Fusion for Composed Image RetrievalProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657727(229-239)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657727

Index Terms

QuickCSGModeling: Quick CSG Operations Based on Fusing Signed Distance Fields for VR Modeling
1. Computing methodologies
  1. Computer graphics
    1. Shape modeling
      1. Mesh models
  2. Modeling and simulation
    1. Model development and analysis
      1. Modeling methodologies
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Virtual reality

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Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 20, Issue 7

July 2024

973 pages

EISSN:1551-6865

DOI:10.1145/3613662

Editor:
Abdulmotaleb El Saddik
Mohamed Bin Zayed University of Artificial Intelligence, UAE and University of Ottawa, Canada

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Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 March 2024

Online AM: 24 May 2023

Accepted: 22 May 2023

Revised: 18 April 2023

Received: 31 July 2022

Published in TOMM Volume 20, Issue 7

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Cited By

Wen HSong XChen XWei YNie LChua THui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Simple but Effective Raw-Data Level Multimodal Fusion for Composed Image RetrievalProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657727(229-239)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657727

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