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Image-driven simplification

Authors:

Peter Lindstrom,

Greg TurkAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 19, Issue 3

Pages 204 - 241

https://doi.org/10.1145/353981.353995

Published: 01 July 2000 Publication History

Abstract

We introduce the notion of image-driven simplification, a framework that uses images to decide which portions of a model to simplify. This is a departure from approaches that make polygonal simplification decisions based on geometry. As with many methods, we use the edge collapse operator to make incremental changes to a model. Unique to our approach, however, is the use at comparisons between images of the original model against those of a simplified model to determine the cost of an ease collapse. We use common graphics rendering hardware to accelerate the creation of the required images. As expected, this method produces models that are close to the original model according to image differences. Perhaps more surprising, however, is that the method yields models that have high geometric fidelity as well. Our approach also solves the quandary of how to weight the geometric distance versus appearance properties such as normals, color, and texture. All of these trade-offs are balanced by the image metric. Benefits of this approach include high fidelity silhouettes, extreme simplification of hidden portions of a model, attention to shading interpolation effects, and simplification that is sensitive to the content of a texture. In order to better preserve the appearance of textured models, we introduce a novel technique for assigning texture coordinates to the new vertices of the mesh. This method is based on a geometric heuristic that can be integrated with any edge collapse algorithm to produce high quality textured surfaces.

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Cited By

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https://dl.acm.org/doi/10.1145/3687905
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Li YQi YWang CBao Y(2023)A Cluster-Based 3D Reconstruction System for Large-Scale ScenesSensors10.3390/s2305237723:5(2377)Online publication date: 21-Feb-2023
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Index Terms

Image-driven simplification
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision representations
        Hierarchical representations
  2. Computer graphics
2. Software and its engineering
  1. Software notations and tools
    1. Development frameworks and environments
      1. Object oriented frameworks

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 19, Issue 3

July 2000

79 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/353981

Editor:
Jessica Hodgins

Issue’s Table of Contents

Copyright © 2000 ACM.

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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Publication History

Published: 01 July 2000

Published in TOG Volume 19, Issue 3

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Cited By

Zhang RPan SLv CGong MHuang H(2024)Architectural Co-LOD GenerationACM Transactions on Graphics10.1145/368790543:6(1-16)Online publication date: 19-Dec-2024
https://dl.acm.org/doi/10.1145/3687905
Wu TYang FFarooq UHao HLi YDiao G(2024)A new point cloud simplification method for reducing visual distortionMeasurement10.1016/j.measurement.2024.114400(114400)Online publication date: Mar-2024
https://doi.org/10.1016/j.measurement.2024.114400
Li YQi YWang CBao Y(2023)A Cluster-Based 3D Reconstruction System for Large-Scale ScenesSensors10.3390/s2305237723:5(2377)Online publication date: 21-Feb-2023
https://doi.org/10.3390/s23052377
Wu JLin YLu D(2023)DR-Occluder: Generating Occluders Using Differentiable RenderingACM Transactions on Graphics10.1145/361834642:6(1-14)Online publication date: 5-Dec-2023
https://dl.acm.org/doi/10.1145/3618346
Maggiordomo AMoreton HTarini M(2023)Micro-Mesh ConstructionACM Transactions on Graphics10.1145/359244042:4(1-18)Online publication date: 26-Jul-2023
https://dl.acm.org/doi/10.1145/3592440
Chen ZPan ZWu KVouga EGao X(2023)Robust Low-Poly Meshing for General 3D ModelsACM Transactions on Graphics10.1145/359239642:4(1-20)Online publication date: 26-Jul-2023
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Chen Y(2023)A progressive mesh simplification algorithm based on neural implicit representationComputational Intelligence10.1111/coin.1260540:1Online publication date: 12-Oct-2023
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