Robust and accurate visual echo cancelation in a full-duplex projector-camera system

Miao Liao, Ruigang Yang, Zhengyou Zhang

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


In this paper we study the problem of "visual echo" in a full-duplex projector-camera system for tele-collaboration applications. Visual echo is defined as the appearance of projected contents observed by the camera. It can potentially saturate the projected contents, similar to audio echo in telephone conversation. Our approach to visual echo cancelation includes an off-line calibration procedure that records the geometric and photometric transfer between the projector and the camera in a look-up table. During run-time, projected contents in the captured video are identified using the calibration information and suppressed, therefore achieving the goal of canceling visual echo. Our approach can accurately handle full color images under arbitrary reflectance of display surfaces and photometric response of the projector or camera. It is robust to geometric registration errors and quantization effect, therefore particularly effective for high-frequency contents such as texts and hand drawings. We demonstrate the effectiveness of our approach with a variety of real images in a full-duplex projector-camera system.

Original languageEnglish
Pages (from-to)1831-1840
Number of pages10
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number10
StatePublished - 2008

Bibliographical note

Funding Information:
The authors would like to thank Mingxuan Sun and Hanning Zhou for working on an early prototype of the visual echo cancellation system. This work is supported in part by the University of Kentucky Research Foundation and the US National Science Foundation Award IIS-0448185.


  • Collaboration
  • Geometric calibration
  • Photometric calibration
  • Projector-camera system
  • Teleconferencing
  • Visual echo cancellation
  • Whiteboard-camera system

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics


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