Motion segmentation for tracking small floating targets in IR video

In the domain of mine-warfare, the detection of targets floating on the surface has remained difficult to automate. Nevertheless, experience in the Persian Gulf has proved that unmoored floating mines are a realistic threat to shipping traffic. An automated system capable of detecting these and other free-floating small objects, using readily available sensors, would prove to be a valuable mine-warfare asset, and could double as a collision avoidance mechanism, salvaging tool or search-and-rescue aid. We have obtained test footage taken with both 3-5 and 8-12m IR cameras of various practice targets, in various environmental conditions. An optical flow sequence is extracted from the IR video sequence, which is subsequently segmented. Motion characteristics are extracted by applying the Proesmans optical flow algorithm to the IR video sequence, calculating and then segmenting the motion field of each subsequent pair of images. A time series of these motion fields allows us to classify different segments according to their motion characteristics and continuity, and thus to detect and track the floating mines.