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SweepCanvas: Sketch-based 3D Prototyping on an RGB-D Image

Published: 20 October 2017 Publication History

Abstract

The creation of 3D contents still remains one of the most crucial problems for the emerging applications such as 3D printing and Augmented Reality. In Augmented Reality, how to create virtual contents that seamlessly overlay with the real environment is a key problem for human-computer interaction and many subsequent applications. In this paper, we present a sketch-based interactive tool, which we term emph{SweepCanvas}, for rapid exploratory 3D modeling on top of an RGB-D image. Our aim is to offer end-users a simple yet efficient way to quickly create 3D models on an image. We develop a novel sketch-based modeling interface, which takes a pair of user strokes as input and instantly generates a curved 3D surface by sweeping one stroke along the other. A key enabler of our system is an optimization procedure that extracts pairs of spatial planes from the context to position and sweep the strokes. We demonstrate the effectiveness and power of our modeling system on various RGB-D data sets and validate the use cases via a pilot study.

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cover image ACM Conferences
UIST '17: Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology
October 2017
870 pages
ISBN:9781450349819
DOI:10.1145/3126594
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 ACM 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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Published: 20 October 2017

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Author Tags

  1. modeling in context
  2. sketch-based modeling
  3. swept surfaces

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UIST '17 Paper Acceptance Rate 73 of 324 submissions, 23%;
Overall Acceptance Rate 561 of 2,567 submissions, 22%

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  • (2024)Neural Canvas: Supporting Scenic Design Prototyping by Integrating 3D Sketching and Generative AIProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642096(1-18)Online publication date: 11-May-2024
  • (2023)VideoDoodles: Hand-Drawn Animations on Videos with Scene-Aware CanvasesACM Transactions on Graphics10.1145/359241342:4(1-12)Online publication date: 26-Jul-2023
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