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. This improvement is based on a new temporal signature: motion barcode for lines. Motion barcode 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 only to lines having similar barcodes. The use of motion barcodes leads to increased speed, accuracy, and robustness in computing the epipolar geometry.

Camera Calibration by Global Constraints on the Motion of Silhouettes

“…We compared our method with the state-of-the-art approaches of Ben-Artzi et al [7] and Sinha et al [33]. For accurate comparisons, we followed the exact same procedures as in Ben-Artzi et al [7]. The fundamental matrix F was computed by RANSAC-based sampling, based on the putative points correspondences.…”

“…They used RANSAC for extracting the most plausible solution. Ben-Artzi et al [7] proposed a temporal binary descriptor, denoted as a motionbarcode, for suggesting the corresponding epipolar lines across views. They sampled the lines from the tangent envelope according to the similarity induced by their descriptor.…”

“…We used the similarity proposed by the binary motionbarcode descriptor [7] as one of the cues for our algorithm. Similar motion-based binary descriptors have been proposed and used by [15], [14].…”

“…It is the input to our similarity estimator. It was used in [7,26,8], which also provides a detailed description. The similarity measure is based on a descriptor denoted as motion barcode.…”

“…These methods match tangent epipolar lines on the convex hull of the silhouettes across views [33]. For each frame, a similarity function for every possible matching of the corresponding tangent epipolar lines is evaluated and the pair with the highest similarity is selected as a putative correspondence [7]. Recovering the corresponding tangent epipolar lines induces matching between the projections of special points, denoted as extremal frontier points, across views where occlusions do not occur (see [19,33,12,28] for a detailed description).…”