A Tracker for Broken and Closely-Spaced Lines

Abstract : We propose an automatic line tracking method which can deal with broken or closely-spaced line segments more accurately than previous methods over an image sequence. The method uses both grey scale information of the original images and geometric attributes of line segments. By using our hierarchical optical flow technique, we can get a good prediction of line segments in a consecutive frame even with large motion. The line attribute of direction, not the orientation, discriminates closely-spaced line segments because when lines are crowded or closely-spaced, their directions are opposite in many cases, even though their orientations are the same. A proposed new matching cost function enables us to deal with multiple collinear line segment matching easily instead of using one-to-one matching. Experiments using real image sequences taken by a hand-held camcorder show that our method is robust against line extraction problems, closely-spaced lines, and large motion.