Environment modelling using spherical stereo imaging

We propose an environment modelling method using high-resolution spherical stereo colour imaging. We capture indoor or outdoor scenes with line scanning by a rotating spherical camera and recover depth information from a stereo image pair using correspondence matching and spherical cross-slits stereo geometry. The existing single spherical imaging technique is extended to stereo geometry and a hierarchical PDE-based sub-pixel disparity estimation method for large images is proposed. The estimated floating-point disparity fields are used for generating an accurate and smooth depth. Finally, the 3D environments were reconstructed using triangular meshes from the depth field. Through experiments, we evaluate the accuracy of reconstruction against ground-truth and analyze the behaviour of errors for spherical stereo imaging.

[1]  Naokazu Yokoya,et al.  3D modeling of outdoor environments by integrating omnidirectional range and color images , 2005, Fifth International Conference on 3-D Digital Imaging and Modeling (3DIM'05).

[2]  Shenchang Eric Chen,et al.  QuickTime VR: an image-based approach to virtual environment navigation , 1995, SIGGRAPH.

[3]  Ryad Benosman,et al.  Panoramic stereovision sensor , 1998 .

[4]  Takeo Kanade,et al.  Virtualized Reality: Constructing Virtual Worlds from Real Scenes , 1997, IEEE Multim..

[5]  Avinash C. Kak,et al.  Vision for Mobile Robot Navigation: A Survey , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Shree K. Nayar,et al.  Catadioptric omnidirectional camera , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[7]  Hans-Peter Seidel,et al.  PDE-Based Anisotropic Disparity-Driven Stereo Vision , 2008, VMV.

[8]  Yoonsik Choe,et al.  Disparity estimation using a region-dividing technique and energy-based regularization , 2004 .

[9]  Yael Pritch,et al.  Omnistereo: Panoramic Stereo Imaging , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Joachim Weickert,et al.  Reliable Estimation of Dense Optical Flow Fields with Large Displacements , 2000, International Journal of Computer Vision.

[11]  Shigang Li,et al.  Full-View Spherical Image Camera , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[12]  Jitendra Malik,et al.  Modeling and Rendering Architecture from Photographs: A hybrid geometry- and image-based approach , 1996, SIGGRAPH.

[13]  Joachim Weickert,et al.  A Review of Nonlinear Diffusion Filtering , 1997, Scale-Space.

[14]  Joachim Weickert,et al.  Optic Flow Goes Stereo: A Variational Method for Estimating Discontinuity-Preserving Dense Disparity Maps , 2005, DAGM-Symposium.

[15]  Daphna Weinshall,et al.  Realtime IBR with omnidirectional crossed-slits projection , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[16]  Allen R. Hanson,et al.  Fast construction of dynamic and multi-resolution 360 degrees panoramas from video sequences , 2006, Image Vis. Comput..

[17]  Yasushi Yagi,et al.  Omnidirectional imaging with hyperboloidal projection , 1993, Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93).

[18]  Richard Szeliski,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, International Journal of Computer Vision.

[19]  Edward H. Adelson,et al.  The Laplacian Pyramid as a Compact Image Code , 1983, IEEE Trans. Commun..

[20]  Shigang Li.  Real-Time Spherical Stereo , 2006, ICPR.

[21]  Edward M. Riseman,et al.  Image-based homing , 1992 .

[22]  Yasushi Yagi,et al.  Real-time omnidirectional image sensor (COPIS) for vision-guided navigation , 1994, IEEE Trans. Robotics Autom..