MULTI-SCALE ANALYSIS OF COLOR AND TEXTURE FOR SALIENT OBJECT DETECTION

被引：0

作者：

Tang, Ketan ^{[1
]}

Au, Oscar C. ^{[1
]}

Fang, Lu ^{[1
]}

Yu, Zhiding ^{[1
]}

Guo, Yuanfang ^{[1
]}

机构：

[1] Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Hong Kong, Hong Kong, Peoples R China

来源：

2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2011年

关键词：

salient object detection; multi-scale analysis; online learning; color; texture;

D O I：

暂无

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：

In this paper we propose a multi-scale segment-based framework for salient object detection. In this framework texture and color features are used together to provide diverse information of salient object. Segmentation is performed on three different scales so that the object boundary can be accurately captured with high probability. Besides, we propose a novel adaptive feature combination mechanism to combine the saliency maps produced with different features, in which the combining weight of each saliency map is learned using online learning. Experiment results demonstrate that the proposed method significantly outperforms the state-of-the-are methods.

引用

页数：4