Placing Arbitrary Objects in a Real Scene Using a Color Cube for Pose Estimation

We describe an Augmented Reality system using the corners of a color cube for camera calibration. In the augmented image the cube is replaced by a computer generated virtual object. The cube is localized in an image by the CSC color segmentation algorithm. The camera projection matrix is estimated with a linear method that is followed by a nonlinear refinement step. Because of possible missclassifications of the segmented color regions and the minimum number of point correspondences used for calibration, the estimated pose of the cube may be very erroneous for some frames; therefore we perform outlier detection and treatment for rendering the virtual object in an acceptable manner.

[1]  William H. Press,et al.  The Art of Scientific Computing Second Edition , 1998 .

[2]  Emanuele Trucco,et al.  Introductory techniques for 3-D computer vision , 1998 .

[3]  Yongduek Seo,et al.  Calibration-Free Augmented Reality in Perspective , 2000, IEEE Trans. Vis. Comput. Graph..

[4]  M. Hirose Mixed Reality - Merging Real and Virtual Worlds , 1999 .

[5]  Carlo Tomasi,et al.  Representation issues in the ML estimation of camera motion , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[6]  Lutz Priese,et al.  Fast and Robust Segmentation of Natural Color Scenes , 1998, ACCV.

[7]  David E. Breen,et al.  Automated Camera Calibration and 3D Egomotion Estimation for Augmented Reality Applications , 1997, CAIP.

[8]  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..

[9]  Yi-Ping Hung,et al.  New calibration-free approach for augmented reality based on parameterized cuboid structure , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[10]  John E. Markel,et al.  Linear Prediction of Speech , 1976, Communication and Cybernetics.

[11]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[12]  Heinrich Niemann,et al.  Using Quaternions for Parametrizing 3-D Rotations in Unconstrained Nonlinear Optimization , 2001, VMV.

[13]  John E. Dennis,et al.  Numerical methods for unconstrained optimization and nonlinear equations , 1983, Prentice Hall series in computational mathematics.

[14]  O. Faugeras Three-dimensional computer vision: a geometric viewpoint , 1993 .