Moving object extraction using a shape-constraint-based splitting active contour model

Miki Haseyama, Yukinori Yokoyama

Abstract: This paper proposes an efficient moving object extraction method based on an active contour model, which is usually called a Snake. The previous Snakes cannot extract multiple objects inside one contour, since they require that one initial contour can only include one object. Such a restriction becomes a problem for moving object extraction application, because an initial contour may contain more than one object including not only the extraction target but also other objects. To deal with this kind of problem, the proposed method utilizes a new splitting mechanism. By incorporating this mechanism, the proposed Snake can successfully extract each of the multiple objects located inside one initial contour. The experiments of extracting moving vehicles from actual image sequences verify the effectiveness and high performance of the proposed method.