research-article

Zenith object detector (ZOD): a multi-camera 3D body scanning platform

Authors:

Dan Collins,

Josh Gigantino,

Aubrey WignerAuthors Info & Claims

SIGGRAPH '14: ACM SIGGRAPH 2014 Studio

Article No.: 43, Page 1

https://doi.org/10.1145/2619195.2656331

Published: 27 July 2014 Publication History

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Abstract

This project introduces a procedure for creating 3D full body scans utilizing a low-cost commodity-based infra-red(IR) sensor and multiple consumer grade cameras. The project, entitled The Zenith Object Detector, uses a home built series of concentric octagons to mount both Asus Xtion structured IR light sensors with color capture capacity, as well as the 16--28 digital cameras for instantaneous image capture. Subjects are scanned in via the Xtions by standing on a rotating platform while the octagons move up from the floor. Simultaneously, the cameras will capture the pose for later 3D reconstruction using 123D Catch, a free Autodesk service for turning images into 3D objects. The outputs will be sent to 3D printers to produce portrait pieces.

References

[1]

Izadi, S., Kim, D., Hilliges, O., et al. 2011. KinectFusion: Real-time 3D Reconstruction and Interaction Using a Moving Depth Camera. ACM Symposium on User Interface Software and Technology, October.

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[2]

Slabaugh, G., Culbertson, B., Malzbender, T., & Schafer, R. (2001, June). A survey of methods for volumetric scene reconstruction from photographs. In Proceedings of the 2001 Eurographics conference on Volume Graphics (pp. 81--101). Eurographics Association.

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Zenith object detector (ZOD): a multi-camera 3D body scanning platform
1. Computing methodologies
  1. Computer graphics

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SIGGRAPH '14: ACM SIGGRAPH 2014 Studio

July 2014

201 pages

ISBN:9781450329774

DOI:10.1145/2619195

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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Association for Computing Machinery

New York, NY, United States

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Published: 27 July 2014

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SIGGRAPH '14: Special Interest Group on Computer Graphics and Ineractive Techniques Conference

August 10 - 14, 2014

Vancouver, Canada

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Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

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Object Tracking by Maximizing Classification Score of Detector Based on Rectangle Features

Robust object tracking via multi-cue fusion

Moving object extraction with cooperative cameras

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