The study of calibration and epipolar geometry for the stereo vision system built by fisheye lenses

Baofeng Zhang; Chunfang Lu; Juha Röning; Weijia Feng

doi:10.1117/12.2079033

8 February 2015 The study of calibration and epipolar geometry for the stereo vision system built by fisheye lenses

Baofeng Zhang, Chunfang Lu, Juha Röning, Weijia Feng

Proceedings Volume 9406, Intelligent Robots and Computer Vision XXXII: Algorithms and Techniques; 94060M (2015) https://doi.org/10.1117/12.2079033
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

Abstract

Fish-eye lens is a kind of short focal distance (f=6~16mm) camera. The field of view (FOV) of it is near or even exceeded 180×180 degrees. A lot of literatures show that the multiple view geometry system built by fish-eye lens will get larger stereo field than traditional stereo vision system which based on a pair of perspective projection images. Since a fish-eye camera usually has a wider-than-hemispherical FOV, the most of image processing approaches based on the pinhole camera model for the conventional stereo vision system are not satisfied to deal with the applications of this category of stereo vision which built by fish-eye lenses. This paper focuses on discussing the calibration and the epipolar rectification method for a novel machine vision system set up by four fish-eye lenses, which is called Special Stereo Vision System (SSVS). The characteristic of SSVS is that it can produce 3D coordinate information from the whole global observation space and acquiring no blind area 360º×360º panoramic image simultaneously just using single vision equipment with one time static shooting. Parameters calibration and epipolar rectification is the basic for SSVS to realize 3D reconstruction and panoramic image generation.

Citation Download Citation

Baofeng Zhang, Chunfang Lu, Juha Röning, and Weijia Feng "The study of calibration and epipolar geometry for the stereo vision system built by fisheye lenses", Proc. SPIE 9406, Intelligent Robots and Computer Vision XXXII: Algorithms and Techniques, 94060M (8 February 2015); https://doi.org/10.1117/12.2079033

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