Fundamental Matrices from Moving Objects Using Line Motion Barcodes
This addresses a challenge in computer vision for applications like surveillance or robotics, but it is incremental as it builds on existing assumptions and methods.
The paper tackles the problem of computing epipolar geometry between cameras with very different viewpoints in scenes with multiple moving objects, by extending prior methods to use Motion Barcodes for finding corresponding epipolar lines, resulting in a method that works in such complex scenes.
Computing the epipolar geometry between cameras with very different viewpoints is often very difficult. The appearance of objects can vary greatly, and it is difficult to find corresponding feature points. Prior methods searched for corresponding epipolar lines using points on the convex hull of the silhouette of a single moving object. These methods fail when the scene includes multiple moving objects. This paper extends previous work to scenes having multiple moving objects by using the "Motion Barcodes", a temporal signature of lines. Corresponding epipolar lines have similar motion barcodes, and candidate pairs of corresponding epipoar lines are found by the similarity of their motion barcodes. As in previous methods we assume that cameras are relatively stationary and that moving objects have already been extracted using background subtraction.