Visual echo cancellation in a projector-camera-whiteboard system

We propose to incorporate a whiteboard into a projector-camera system. The whiteboard serves as the writing surface (input) as well as the projecting surface (output). The ability to write and draw on top of computer-projected content opens up many new opportunities for real-time collaborations between people located on-site and remotely. Such applications inevitably require extracting handwritings from video images that contain both handwritings and the projected content. By analogy with echo cancellation in audio conferencing, we call this problem visual echo cancellation. This paper presents one approach to accomplish the task. Our visual echo cancellation algorithm estimates the incident light and derives the surface albedo based on both incident light and reflection. By estimating the albedo, we can extract the writings and recover their colors. Our approach includes two basic components of projector-camera systems: geometric calibration and color calibration. The first one solves the mapping between the position in the camera view and the position in the projector screen, while the second one solves the mapping between the actual color of the projected content and that seen by the camera.

[1]  Jianbo Shi,et al.  Tele-Graffiti: A Camera-Projector Based Remote Sketching System with Hand-Based User Interface and Automatic Session Summarization , 2003, International Journal of Computer Vision.

[2]  Eric Saund Bringing the Marks on a Whiteboard to Electronic Life , 1999, CoBuild.

[3]  Ramesh Raskar,et al.  Seamless multi-projector display on curved screens , 2003 .

[4]  Rahul Sukthankar,et al.  Smarter presentations: exploiting homography in camera-projector systems , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[5]  Pierre David Wellner,et al.  Interacting with paper on the DigitalDesk , 1993, CACM.

[6]  Paul A. Beardsley,et al.  A self-correcting projector , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[7]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[8]  François Bérard,et al.  The Magic Table: Computer-Vision Based Augmentation of a Whiteboard for Creative Meetings , 2003 .

[9]  R. Y. Tsai,et al.  An Efficient and Accurate Camera Calibration Technique for 3D Machine Vision , 1986, CVPR 1986.

[10]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Greg Welch,et al.  The office of the future: a unified approach to image-based modeling and spatially immersive displays , 1998, SIGGRAPH.

[12]  James L. Crowley,et al.  Perceptual user interfaces: things that see , 2000, CACM.

[13]  Bernd Fröhlich,et al.  The Responsive Workbench: A Virtual Work Environment , 1995, Computer.