[1] |
Loupias E, Sebe N, Bres S, Jolion J M. Wavelet-based salient points for image retrieval. In:Proceedings of the 2000 IEEE International Conference on Image Processing. Vancouver, British Columbia, Canada:IEEE, 2000, 2:518-521 |
[2] |
[2] Jian M W, Dong J Y, Ma J. Image retrieval using wavelet-based salient regions. The Imaging Science Journal, 2011, 59(4):219-231 |
[3] |
[3] Guo C L, Zhang L M. A novel multi-resolution spatiotemporal saliency detection model and its applications in image and video compression. IEEE Transactions on Image Processing, 2010, 19(1):185-198 |
[4] |
[4] Kim W, Kim C. A novel image importance model for content-aware image resizing. In:Proceedings of the 18th IEEE International Conference on Image Processing. Brussels, Belguim:IEEE, 2011. 2469-2472 |
[5] |
[5] Gupta R, Chaudhury S. A scheme for attentional video compression. In:Proceedings of the 4th International Conference on Pattern Recognition and Machine Intelligence. Berlin, Heidelberg:Springer-Verlag, 2011. 458-465 |
[6] |
[6] Itti L. Automatic foveation for video compression using a neurobiological model of visual attention. IEEE Transactions on Image Processing, 2004, 13(10):1304-1318 |
[7] |
[7] Kanan C, Cottrell G. Robust classification of objects, faces, and flowers using natural image statistics. In:Proceedings of the 2010 IEEE Conference on Computer Vision and Pattern Recognition. San Francisco, California, USA:IEEE, 2010. 2472-2479 |
[8] |
[8] Teuber H L. Physiological psychology. Annual Review of Psychology, 1955, 6:267-296 |
[9] |
[9] Wolfe J M, Horowitz T S. What attributes guide the deployment of visual attention and how do they do it? Nature Reviews Neuroscience, 2004, 5(6):495-501 |
[10] |
Desimone R, Duncan J. Neural mechanisms of visual selective attention. Annual Review of Neuroscience, 1995, 18(1):193-222 |
[11] |
Mannan S K, Kennard C, Husain M. The role of visual salience in directing eye movements in visual object agnosia. Current Biology, 2009, 19(6):247-248 |
[12] |
Treisman A M, Gelade G. A feature-integration theory of attention. Cognitive Psychology, 1980, 12(1):97-136 |
[13] |
Koch C, Ullman S. Shifts in selective visual attention:towards the underlying neural circuitry. Human Neurobiology, 1985, 4(4):219-227 |
[14] |
Itti L, Koch C, Niebur E. A model of saliency-based visualattention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(11):1254-1259 |
[15] |
Harel J, Koch C, Perona P. Graph-based visual saliency. In:Proceedings of the 2006 Advances in Neural Information Processing Systems. Vancouver, British Columbia, Canada:Bradford Book, 2006. 545-552 |
[16] |
Hansen L K, Karadogan S, Marchegiani L. What to measure next to improve decision making? On top-down task driven feature saliency. In:Proceedings of the 2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain. Paris, France:IEEE, 2011. 1-7 |
[17] |
Baluch F, Itti L. Mechanisms of top-down attention. Trends in Neurosciences, 2011, 34(4):210-224 |
[18] |
Itti L, Koch C. Computational modelling of visual attention. Nature Reviews Neuroscience, 2001, 2(3):194-203 |
[19] |
Judd T, Ehinger K, Durand F, Torralba A. Learning to predict where humans look. In:Proceedings of the 12th IEEE International Conference on Computer Vision. Kyoto, Japan:IEEE, 2009. 2106-2113 |
[20] |
Liu T, Yuan Z, Sun J, Wang J D, Zheng N N, Tang X O, Shun H Y. Learning to detect a salient object. IEEE Transactions on Software Engineering, 2011, 33(2):353-367 |
[21] |
Borji A, Itti L. Exploiting local and global patch rarities for saliency detection. In:Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition. Providence, Rhode Island, USA:IEEE, 2012. 478-485 |
[22] |
Jiang H Z, Wang J D, Yuan Z J, Wu Y, Zheng N N, Li S P. Salient object detection:a discriminative regional feature integration approach. In:Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition. Portland, Oregon, USA:IEEE, 2013. 2083-2090 |
[23] |
Shen X, Wu Y. A unified approach to salient object detection via low rank matrix recovery. In:Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition. Providence, Rhode Island, USA:IEEE, 2012. 853-860 |
[24] |
Yan Q, Xu L, Shi J P, Jia J Y. Hierarchical saliency detection. In:Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition. Portland, Oregon, USA:IEEE, 2013. 1155-1162 |
[25] |
Yang C, Zhang L H, Lu H C, Ruan X, Yang M H. Saliency detection via Graph-Based manifold Ranking. In:Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition. Portland, Oregon, USA:IEEE, 2013. 3166-3173 |
[26] |
Li X H, Lu H C, Zhang L H, Ruan X, Yang M H. Saliency detection via dense and sparse reconstruction. In:Proceedings of the 2013 IEEE International Conference on Computer Vision. Sydney, Australia:IEEE, 2013. 2976-2983 |
[27] |
Hu Y Q, Rajan D, Chia L T. Robust subspace analysis for detecting visual attention regions in images. In:Proceedings of the 13th Annual ACM International Conference on Multimedia. Santa Fe, New Mexico, USA:ACM, 2005. 716-724 |
[28] |
Hou X D, Zhang L. Saliency detection:a spectral residual approach. In:Proceedings of the 2007 IEEE Conference on Computer Vision and Pattern Recognition. Minneapolis, Minnesota State, USA:IEEE, 2007. 1-8 |
[29] |
Guo C L, Ma Q, Zhang L M. Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform. In:Proceedings of the 2008 IEEE Conference on Computer Vision and Pattern Recognition. Anchorage, Alaska, USA:IEEE, 2008. 1-8 |
[30] |
Zhang Qiao-Rong, Gu Guo-Chang, Liu Hai-Bo, Xiao Hui-Min. Salient region detection using multi-scale analysis in the frequency domain. Journal of Harbin Engineering University, 2010, 31(3):361-365(张巧荣, 顾国昌, 刘海波, 肖会敏. 利用多尺度频域分析的图像显著区域检测. 哈尔滨工程大学学报, 2010, 31(3):361-365) |
[31] |
Lafferty J D, McCallum A, Pereira F C N. Conditional random fields:probabilistic models for segmenting and labeling sequence data. In:Proceedings of the 8th IEEE International Conference on Machine Learning. Williamstown, MA, USA:IEEE, 2001. 282-289 |
[32] |
Rother C, Kolmogorov V, Blake A. Grabcut:interactive foreground extraction using iterated graph cuts. ACM Transactions on Graphics, 2004, 23(3):309-314 |
[33] |
Kumar S, Hebert M. Discriminative random fields:a discriminative framework for contextual interaction in classification. In:Proceedings of the 9th IEEE International Conference on Computer Vision. Nice, France:IEEE, 2003, 2:1150-1157 |
[34] |
Cheng M M, Zhang G X, Mitra N J, Huang X L, Hu S M. Global contrast based salient region detection. In:Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition. Colorado Springs, Colorado, USA:2011 IEEE, 2011. 409-416 |
[35] |
Sun J, Lu H C, Li S F. Saliency detection based on integration of boundary and soft-segmentation. In:Proceedings of the 19th IEEE International Conference on Image Processing. Orlando, Florida, USA:IEEE, 2012. 1085-1088 |
[36] |
Wei Y C, Wen F, Zhu W J, Sun J. Geodesic saliency using background priors. In:Proceedings of the 12th European conference on Computer Vision-Volume Part Ⅲ. Berlin, Heidelberg:Springer-Verlag, 2012. 29-42 |
[37] |
Borji A, Sihite D N, Itti L. Salient object detection:A benchmark. In:Proceedings of the 12th European conference on Computer Vision-Volume Part Ⅱ. Berlin, Heidelberg:Springer-Verlag, 2012. 414-429 |
[38] |
Achanta R, Shaji A, Smith K, Lucchi A, Fua P, Ssstrunk S. SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(11):2274-2282 |
[39] |
Achanta R, Hemami S, Estrada F, Susstrunk S. Frequency-tuned salient region detection. In:Proceedings of the 2009 IEEE International Conference on Computer Vision and Pattern Recognition. Miami Beach, Florida, USA:IEEE, 2009. 1597-1604 |
[40] |
Achanta R, Susstrunk S. Saliency detection using maximum symmetric surround. In:Proceedings of the 2010 IEEE International Conference on Image Processing. Hong Kong, China:IEEE, 2010. 2653-2656 |
[41] |
Jain, Anil K. Fundamentals of Digital Image Processing. Englewood Cliffs, New Jersey, USA:Prentice Hall, 1989. 51 |
[42] |
Thomas S W. Efficient inverse color map computation. Graphics Gems Ⅱ. Boston:Academic Press, 1991:116-125 |
[43] |
Otsu N. A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 1979, 9(1):62-66 |
[44] |
Goferman S, Zelnik-Manor L, Tal A. Context-aware saliency detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(10):1915-1926 |
[45] |
Jiang H Z, Wang J D, Yuan Z J, Liu T, Zheng N N. Automatic salient object segmentation based on context and shape prior. In:Proceedings of the 2011 British Machine Vision Conference. Dundee, Scotland, UK:BMVA Press, 2011. 1-12 |
[46] |
Rahtu E, Kannala J, Salo M, Heikkil J. Segmenting salient objects from images and videos. In:Proceedings of the 11th European conference on Computer Vision-Part V. Berlin, Heidelberg:Springer-Verlag, 2010. 366-379 |