Multimodal 3D panoramic imaging using a precise rotating platform

Both panoramic and multimodal imaging are becoming more and more desirable in applications such as wide area surveillance, robotics, mapping and entertainment. In this paper, we build a precise rotating platform to generate co-registered multimodal and multiview 3D panoramic images. The platform consists of a pair of color and thermal cameras that are mounted with their optical axes pointing away from the rotation center. As a result of the precisely controlled rotation of the platform, multiview panoramic mosaics of color and thermal images can be obtained using circular perspective projection. Furthermore, the mosaics of two modalities can be precisely aligned via the analysis of their geometric relationship. In order to estimate the parameters of the cameras needed for multimodal alignment, a calibration method that is very simple to implement is proposed based on the relationship of the distance and angle of a feature point coming in and out of the field-of-view of a camera. Experimental results for multiview and multimodal alignment of stereo panoramas are given.

[1]  Saburo Tsuji,et al.  Panoramic representation for route recognition by a mobile robot , 1992, International Journal of Computer Vision.

[2]  Shmuel Peleg,et al.  Multi-sensor super-resolution , 2002, Sixth IEEE Workshop on Applications of Computer Vision, 2002. (WACV 2002). Proceedings..

[3]  Wei Jiang,et al.  Panoramic 3D Reconstruction Using Rotational Stereo Camera with Simple Epipolar Constraints , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[4]  Allen R. Hanson,et al.  Generalized parallel-perspective stereo mosaics from airborne video , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Robert C. Bolles,et al.  Epipolar-plane image analysis: An approach to determining structure from motion , 1987, International Journal of Computer Vision.

[6]  Shree K. Nayar,et al.  A Theory of Single-Viewpoint Catadioptric Image Formation , 1999, International Journal of Computer Vision.

[7]  M.H. Ang,et al.  Appearance-based SLAM with map loop closing using an omnidirectional camera , 2007, 2007 IEEE/ASME international conference on advanced intelligent mechatronics.

[8]  Hong Chang,et al.  Multispectral visible and infrared imaging for face recognition , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

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

[10]  Aggelos K. Katsaggelos,et al.  A multicamera setup for generating stereo panoramic video , 2005, IEEE Transactions on Multimedia.

[11]  Diego A. Socolinsky,et al.  Design and Deployment of Visible-Thermal Biometric Surveillance Systems , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[12]  Harry Shum,et al.  Stereo reconstruction from multiperspective panoramas , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Narendra Ahuja,et al.  Panoramic image acquisition , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[14]  Cedric Nishan Canagarajah,et al.  Adaptive Region-Based Multimodal Image Fusion Using ICA Bases , 2006, 2006 9th International Conference on Information Fusion.

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

[16]  M. Hild,et al.  Image registration in stereo-based multi-modal imaging systems , 2005, ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005..

[17]  Javier Civera,et al.  Drift-Free Real-Time Sequential Mosaicing , 2009, International Journal of Computer Vision.

[18]  J. Meguro,et al.  Development of positioning technique using omni-directional IR camera and aerial survey data , 2007, 2007 IEEE/ASME international conference on advanced intelligent mechatronics.