Title :
Visual attention model based on multi-scale local contrast of low-level features
Author :
Zhang, Jie ; Sun, Jiande ; Liu, Ju ; Yang, Caixia ; Yan, Hua
Author_Institution :
Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan, China
Abstract :
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.
Keywords :
image representation; eye tracking system; human vision; image representation; multiscale local contrast; salient region detection; visual attention model; Biological system modeling; Computational modeling; Feature extraction; Frequency modulation; Humans; Image color analysis; Visualization; interest region; local contrast; multi-scale transform; salient region; visual attention;
Conference_Titel :
Signal Processing (ICSP), 2010 IEEE 10th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5897-4
DOI :
10.1109/ICOSP.2010.5656042