Visual Attention Model Based on Multi-Scale Local Contrast of Low-Level Features

摘要：

Salient regions detection is becoming more and more important due to its useful application in image representation and understanding. The accurate detection of salient regions can reduce the complexity and improve the efficiency of image processing. In this paper, a visual attention model based on multi-scale local contrast of low level features is proposed. In the proposed model, a multi-scale transform is used to obtain the original image at different scales, and the local contrast features of intensity, texture and color are calculated at each scale. Then these contrast features are interpolated iteratively to form three feature maps corresponding to intensity, texture and color respectively. Finally, the feature maps are integrated to obtain the final salient regions. In the experiment, a proven eye tracking system is used and verifies the salient region detected by the proposed model consistent with human vision. Furthermore, comparing with another two existing models, the proposed model also shows better performance.

关键词： salient region interest region visual attention local contrast multi-scale transform

作者: Jie Zhang Jiande Sun Ju Liu Caixia Yang Hua Yan

作者单位: School of Information Science and Engineering, Shandong University, Jinan 250100, P.R.China Computer Science and Technology School, Shandong Economic University, Jinan 250014, P.R.China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 902-905

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）