Active contours based tracking methods have widely used for object tracking due to their following advantages. 1) effectiveness
to descript complex object boundary, and 2) ability to track the dynamic object boundary. However their tracking results are
very sensitive to location of the initial curve. Initial curve far form the object induces more heavy computational cost,
low accuracy of results, as well as missing the highly active object. Therefore, this paper presents an object tracking method
using a mean shift algorithm and active contours. The proposed method consists of two steps: object localization and object
extraction. In the first step, the object location is estimated using mean shift. And the second step, at the location, evolves
the initial curve using an active contour model. To assess the effectiveness of the proposed method, it is applied to synthetic
sequences and real image sequences which include moving objects.