Computer Science Department
School of Computer Science, Carnegie Mellon University
A Tracker for Broken and Closely-Spaced Lines
Naoki Chiba, Takeo Kanade
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.