A single-camera stereo vision system offers a greatly simplified approach to image capture and analysis. In the original
study by Lovegrove and Brame, they proposed a novel optical system that uses a single camera to capture two short,
wide stereo images that can then be analyzed for real-time obstacle detection. In this paper, further analysis and
refinement of the optical design results in two virtual cameras with perfectly parallel central axes. A new prototype
camera design provides experimental verification of the analysis and also provides insight into practical construction.
The experimental device showed that the virtual cameras' axes possessed a deviation from parallel of less than 12
minutes (or 0.2°). The calculation of distances to objects from the two overlapping images all showed errors smaller than
the pixel resolution limitation. In addition, a barrel lens correction was used in processing the image to allow parallax
distance determination in the whole horizontal view of the images.
Stereo vision is attractive for autonomous mobile robot navigation, but the cost and complexity of stereo camera systems and the computational requirements make full stereo vision impractical. A novel optical system allows the capture of a pair of short, wide stereo images from a single camera, which are then processed to detect vertical edges and infer obstacle positions and locations within the planar field of view, providing real-time obstacle detection. Our optical system involves a pair of right-angle prisms stacked vertically, splitting the camera field of view vertically in half. Right angle mirrors on either side redirect the image forward but at a horizontally displaced location, creating two virtual cameras. Tilting these mirrors provides an overlapping image area. Alternately, tilting the prisms produces the same effect. This image area is wide but not very tall. However, in a mobile robot scenario the majority of obstacles of interest intersect this field of view.
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