Robust segmentation of moving objects in video based on spatiotemporal visual saliency and active contour model

被引：7

作者：

Ramadan, Hiba ^{[1
]}

Tairi, Hamid ^{[1
]}

机构：

[1] Univ Sidi Mohamed Ben Abdellah, Dept Informat, Fac Sci Dhar Mahraz, BP 1796 Atlas Fez, Fes 30000, Morocco

来源：

JOURNAL OF ELECTRONIC IMAGING | 2016年 / 25卷 / 06期

关键词：

segmentation; moving object; visual saliency; optical flow; convex active contour; EXTRACTION; TRACKING;

D O I：

10.1117/1.JEI.25.6.061612

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents an algorithm for automatic segmentation of moving objects in video based on spatiotemporal visual saliency and an active contour model. Our algorithm exploits the visual saliency and motion information to build a spatiotemporal visual saliency map used to extract a moving region of interest. This region is used to automatically provide the seeds for the convex active contour (CAC) model to segment the moving object accurately. The experiments show a good performance of our algorithm for moving object segmentation in video without user interaction, especially on the SegTrack dataset. (C) 2016 SPIE and IS&T

引用

页数：10

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