A tracker for broken and closely spaced lines

We propose an automatic line tracking method which is robust in tracking broken and closely-spaced line segments over an image sequence. The method uses both the grey-level information of original images and the geometric attributes of line segments. By using a hierarchical opticalow estimation technique, we can obtain a good prediction of line segment motion in a consecutive frame. There remains the need to distinguish closely-spaced lines which are common in man-made objects. Discrimination of these lines is achieved by use of a direction attribute rather than an orientation attribute. Due to line extraction problems, a single line segment may be broken into several segments. A proposed matching similarity function enables us to perform multiple collinear-line segment matching, instead of merely one-to-one matching. Experiments using noisy and complicated real image sequences taken with a hand-held camcorder con rm the robustness of our method in di cult tasks.