2005 IEEE International Conference on Multimedia and Expo
Adaptive local context suppression of multiple cues for salient visual attention detection
Amsterdam, Netherlands
July 06-July 06
ISBN: 0-7803-9331-7
Y. Hu, Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore
D. Rajan, Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore
L.-T. Chia, Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore
Visual attention is obtained through determination of contrasts of low level features or attention cues like intensity, color etc. We propose a new texture attention cue that is shown to be more effective for images where the salient object regions and background have similar visual characteristics. Current visual attention models do not consider local contextual information to highlight attention regions. We also propose a feature combination strategy by suppressing saliency based on context information that is effective in determining the true attention region. We compare our approach with other visual attention models using a novel average discrimination ratio measure.
Index Terms:
average discrimination ratio measure, adaptive local context suppression, multiple image texture cues, visual attention detection, feature combination strategy
Citation:
Y. Hu, D. Rajan, L.-T. Chia, "Adaptive local context suppression of multiple cues for salient visual attention detection," icme, pp.4 pp., 2005 IEEE International Conference on Multimedia and Expo, 2005