Title :
Spatio-temporal video object segmentation using moving detection and graph cut methods
Author :
Dingming Liu ; Jieyu Zhao
Author_Institution :
Res. Inst. of Comput. Sci. & Technol., Ningbo Univ., Ningbo, China
Abstract :
Segmentation of video foreground objects from background has many important applications, such as human computer interaction, video compression, multimedia content editing and manipulation. From a single video sequence with a moving foreground object and stationary background, this paper propose a novel algorithm to extract video object using graph cut and moving detection methods. The key idea in our paper is to obtain the moving object region which can be set as the possibility foreground, and the other region set as background, then this prior can be used by means of graph cut, video segmentation is then transformed to static image segmentation which can be achieved by binary min-cut.
Keywords :
graph theory; image segmentation; image sequences; object detection; video signal processing; graph cut methods; moving detection methods; spatio-temporal video object segmentation; static image segmentation; video foreground object segmentation; video sequence; Computer vision; Conferences; Image color analysis; Image segmentation; Motion segmentation; Object segmentation; Streaming media; Gibbs Random Field; frame difference; graph cut; moving detection; video segmentation;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022388