In this paper, the main idea is to use the prior knowledge to guide the segmentation. Firstly the continuity among
adjacent frames is used to create a motion template according to the Displaced Frame Difference's (DFD) higher
character . And then the color template is established by using the k-means clustering. Based upon the information
derived from the previous two templates, the segmentation image is defined as foreground, background and boundary
regions. Then, the segmentation problem is formulated as an energy minimization problem. The hard edge of foreground
is then obtained by implementing graph-cut algorithm. Experimental results demonstrate the effectiveness of proposed
algorithm.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.