REVEAL (Reconstruction and Exploratory Visualization: Engineering meets ArchaeoLogy)

An NSF Project consisting of:

  • REVEAL: A System for Streamlined Powerful Sensing, Archiving, Extracting Information from, Visualizing and Communicating, Archaeological Site-excavation Data.  REVEAL is available to the archaeology community.
  • Core Computer-Vision/Pattern-Recognition/Machine-Learning Research with Applications to Archaeology and the Humanities.


 REVEAL Overview

Overview Video



        REVEAL data entry, database, and data analysis:

  REVEAL Analyze Data REVEAL Import Data REVEAL Database

  • 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.



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

Assist reconstruction of architecture using computer vision and computer

graphics techniques.

Reveal Analyzer

The REVEAL Analyzer provides the excavator, researcher, or student with integrated multi-format access to the tables, photographs, and 3d models in the database.  Exploring and filtering the data in plan view, 3D view, photo view, or tabular view generates automatic back-end queries to extract, format, and display relevent information from the database.

Reveal Web

The Reveal Web application is a open source web 2.0 application that runs most platforms and browsers. The current version is primarily a data entry platform. Users could enter archeological data into our databasusing web based grid forms. Photo's and site plan's can also uploaded directly into the database.



Image-based 3D modeling is the problem of recovering
scenes 3D geometry and appearance from images. Nowadays,
with the prevalence of digital cameras, image-based
3D modeling has the clear advantage over other 3D modeling
techniques in terms of equipment availability, affordability
and amount of user input, besides advantages on operation
conditions, scalability, etc.


Kimia, B. B., "HINDSITE: A User-Interactive Framework for Fragment Assembly", Proceedings of CVPR Workshop on Applications of Computer Vision in Archaeology (ACVA'10), June, 2010.  
Gay, E., K. Galor, D. B. Cooper, A. Willis, B. B. Kimia, S. Karumuri, G. Taubin, W. Doutre, D. Sanders, and S. Liu, "REVEAL Intermediate Report", Proceedings of CVPR Workshop on Applications of Computer Vision in Archaeology (ACVA'10), June, 2010.  

Fabbri, R., and B. B. Kimia, "3D Curve Sketch: Flexible Curve-Based Stereo Reconstruction and Calibration", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, California, USA, IEEE Computer Society Press, 2010.  

K. Galor, D. Sanders, and A. Willis, "Semi-automated data capture and image processing: new routes to interactive 3D models", pp.179-88 in Space, Time, Place Third International Conference on Remote Sensing in Archaeology, 17th-21st August 2009, Tiruchirappalli, Tamil Nadu, India, edited by Stefano Campana, Maurizio Forte and Claudia Liuzza (BAR International Series #2118), British Archaeological Reports, 2010






   Senior Person


  • Eben Gay
  • John Ballem

   Grad Students

  • Daniel Cabrini
  • Suman Karumuri                      
  • Will Doutre                                
  • Shubao Liu
  • Osman Ulasoy
  • Fatih Calakli


  REVEAL Kit -

  REVEAL Videos


  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. 

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.