Adaptive graph-cut algorithm to video moving objects segmentation based on Euler´s Elastica Model

Author

Guo Chunsheng ; Gao Haiyan

Author_Institution

Coll. of Commun. Eng., Hangzhou Dianzi Univ., Hangzhou, China

Volume

1

fYear

2011

fDate

15-17 Oct. 2011

Firstpage

394

Lastpage

398

Abstract

The traditional graph-cut algorithm to video moving objects segmentation is based on the low-order MRF. The detected moving objects will be over-smoothing. In this paper, an adaptive graph-cut algorithm to video moving objects segmentation based on Euler´s Elastica Model was proposed. The higher-order moving objects model is used to restrict the shape of moving object. Experimental results show that the proposed method can effectively and stably segment moving objects from the video and can preserve sharp and detail features better than the traditional graph-cut algorithm.

Keywords

graph theory; image motion analysis; image segmentation; object detection; video signal processing; Euler Elastica model; MRF; adaptive graph-cut algorithm; moving object detection; video moving object segmentation; Adaptation models; Algorithm design and analysis; Image segmentation; Mathematical model; Object segmentation; Prediction algorithms; Signal processing algorithms; Euler´s elastica; Graph-cut; Moving objects segmentation; kalman prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing (CISP), 2011 4th International Congress on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-9304-3

Type

conf

DOI

10.1109/CISP.2011.6099905

Filename

6099905