Camera Calibration from Dynamic Silhouettes Using Motion Barcodes

Abstract

Computing the epipolar geometry between cameras with very different viewpoints is often problematic as matching points are hard to find. In these cases, it has been proposed to use information from dynamic objects in the scene for suggesting point and line correspondences. We propose a speed up of about two orders of magnitude, as well as an increase in robustness and accuracy, to methods computing epipolar geometry from dynamic silhouettes based on a new temporal signature, motion barcode for lines. This is a binary temporal sequence for lines, indicating for each frame the existence of at least one foreground pixel on that line. The motion barcodes of two corresponding epipolar lines are very similar so the search for corresponding epipolar lines can be limited to lines having similar barcodes leading to increased speed, accuracy, and robustness in computing the epipolar geometry.