Overview Video
Overview
REVEAL data entry, database, and data analysis:
Automatically co-registers disparate data types – tables, site plan, sketches, images, video, 3D dense-data laser scans. Displays layers of 2D AND 3D data.
Is a platform for sophisticated application- algorithms for reconstruction of objects and architectural structures from fragments, comparison of artifacts across different databases, inferences involving within-trench structure, or landscapes, using pattern-recognition and computer-vision methodologies based on disparate types of data and information.
Is available to the archaeology community as an open source project. Is being developed and maintained by Brown University. Is open to inputs by the archaeology community.
Core CV/PR/ML research:
Estimation of 3D surface, curves, and other geometries from multiviews.
Estimation of the Crusader Citadel at Apollonia-Arsuf, Israel, from site plans, texts, dense-data laser scans, and multiviews.
Automatic or semi-automatic estimation of ceramic pots and glass objects from dense-data laser scans of their broken fragments.
Accurate inexpensive 3D estimation from single-view structured light.
Inexpensive dense-data laser scanner/software for 2 cm or better accuracy at up to 80m distance.
Background
REVEAL is an on-going four-year NSF-funded project promoting paradigm shifts in archaeology. This project will create a total environment for acquiring and presenting archaeological data in a way that streamlines fieldwork processes, rippling through all aspects of data collection, recording, imaging, analysis, and publication to support and enhance the fieldteam’s understanding of the data. REVEAL leverages three aspects of digital technology: computer vision algorithms speed up or replace manual measurement and documentation tasks; computer automation speeds up data entry tasks; and integrated 2D and 3D media enhance data comprehension.
REVEAL is being developed by a consortium of innovators at the Division of Engineering, Laboratory for Man/Machine Systems, Brown University (Providence, Rhode Island, USA); the Department of Electrical and Computer Engineering, the University of North Carolina at Charlotte (North Carolina; USA); the Institute for the Visualization of History (Williamstown, Massachusetts, USA); and Tel Aviv University (Israel).
This project is working toward important accomplishments in computer-vision and pattern-recognition (CVPR) research, as well as in digital archaeology. Our endeavors will offer significant contributions to core CVPR research and to archaeological data-collection and visualization systems. REVEAL presents a major paradigm shift in how archaeologists collect information, visualize artifactual interrelationships, analyze contexts, and disseminate research conclusions.
Reveal Projects
Castle Reconstruction
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Assist reconstruction of architecture using computer vision and computer graphics techniques. |
Reveal Analyzer
Reveal Web
3D
Publications
Personnel
Professors
-
Benjamin Kimia
Professor of Engineering
Phone: +1 401 863 1353
Phone 2: +1 401 863 2177
Benjamin_Kimia@Brown.edu
http://www.lems.brown.edu/kimia.html
David B. Cooper
Professor of Engineering
Phone: +1 401 863 2601
Phone 2: +1 401 863 2177
David_Cooper@Brown.edu
Gabriel Taubin
Associate Professor
Phone: (401)-863-1484
Fax : (401)-863-7670
taubin@brown.edu
http://mesh.brown.edu/taubin
Katarina Galor
Hirschfeld Visiting Assistant Professor of Judaic Studies
Phone: (401)-965-7215
Katharina_Galor@brown.edu
http://research.brown.edu/research/profile.php?id=1106970115
- Andrew Willis http://ece.uncc.edu/~arwillis/
Senior Person
- Donald Sanders http://www.vizin.org/
Staff
- Eben Gay
- John Ballem
Grad Students
- Daniel Cabrini
- Suman Karumuri
- Will Doutre
- Shubao Liu
- Osman Ulasoy
- Fatih Calakli
Links
REVEAL Kit - http://sourceforge.net/projects/revealanalyze/
REVEAL Videos
- Overview - http://www.youtube.com/watch?v=1OJkiEMiMSg
- Data Entry - http://www.youtube.com/watch?v=HLQuJiZ9hWs
- Data Analyzer - http://www.youtube.com/watch?v=MlBWb9B9mh0
Other links
National Science Foundation Aknowledgement
This material is based upon work supported by the National Science Foundation under Grant No.0808718, III-CXT-Core Computer Vision Research: Promoting Paradigm Shifts in Archaeology.
Disclaimer
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.