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Cited by 610

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Articulated mesh animation from multi-view silhouettes

Open access
Vlasic, Daniel, Baran, Ilya, Matusik, Wojciech, Popović, Jovan·2008·ACM Transactions on Graphics

Abstract

Details in mesh animations are difficult to generate but they have great impact on visual quality. In this work, we demonstrate a practical software system for capturing such details from multi-view video recordings. Given a stream of synchronized video images that record a human performance from multiple viewpoints and an articulated template of the performer, our system captures the motion of both the skeleton and the shape. The output mesh animation is enhanced with the details observed in the image silhouettes. For example, a performance in casual loose-fitting clothes will generate mesh animations with flowing garment motions. We accomplish this with a fast pose tracking method followed by nonrigid deformation of the template to fit the silhouettes. The entire process takes less than sixteen seconds per frame and requires no markers or texture cues. Captured meshes are in full correspondence making them readily usable for editing operations including texturing, deformation transfer, and deformation model learning.

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Crossref · 10.1145/1360612.1360696

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Metadata

Authors
Vlasic, D., Baran, I., Matusik, W., & Popović, J.
Venue
ACM Transactions on Graphics
Published
2008-08
Volume
27
Issue
3
Pages
1-9
ISSN
  • 0730-0301 (ISSN-L)
  • 1557-7368
OpenAlex
W2122578066
Cited by
610
References
4
FWCI
45.86
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Articulated mesh animation from multi-view silhouettes. https://app.cochat.ai/papers/10.1145/1360612.1360696
The paper
Vlasic, D., Baran, I., Matusik, W., & Popović, J. (2008). Articulated mesh animation from multi-view silhouettes. ACM Transactions on Graphics. https://doi.org/10.1145/1360612.1360696

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.