Single Camera Stereo for Mobile Robot Surveillance

J. McBride, M. Snorrason, T. Goodsell, R. Eaton, and M. R. Stevens

CVPR Workshop on Advanced 3D Imaging for Safety and Security, San Diego, CA (June, 2005)

Mobile robot designers frequently look to computer vision to solve navigation, obstacle avoidance, and object detection problems such as those encountered in parking lot surveillance. Stereo reconstruction is a useful technique in this domain. The advantage of a single-camera stereo method versus a stereo rig is the flexibility to change the baseline distance to best match each scenario. This directly increases the robustness of the stereo algorithm and increases the effective range of the system. The challenge comes from accurately rectifying the images into an ideal stereo pair. Structure from motion (SFM) can be used to compute the camera motion between the two images, but its accuracy is limited and small errors can cause rectified images to be misaligned. We present a single-camera stereo system that incorporates a Levenberg-Marquardt minimization of rectification parameters to bring the rectified images into alignment.

Features selected in one image are shown as solid dots. Hollow dots show the tracked locations of those features in another image; the goal is to align the features.

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