Borji A, Itti L. State-of-the-art in visual attention modeling. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(1):185-207
[2]
Borji A, Sihite D, Itti L. Quantitative analysis of human-model agreement in visual saliency modeling:a comparative study. IEEE Transactions on Image Processing, 2013, 22(1):55-69
[3]
Koch C, Ullman S. Shifts in selective visual attention:towards the underlying neural circuitry. Human Neurobiology, 1985, 4(4):219-227
[4]
Itti L, Koch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(11):1254-1259
[5]
Ma Y F, Zhang H J. Contrast-based image attention analysis by using fuzzy growing. In:Proceedings of the 11th ACM International Conference on Multimedia. Berkeley, USA:ACM, 2003. 374-381
[6]
Achanta R, Estrada F, Wils P, Süsstrunk S. Salient region detection and segmentation. In:Proceedings of the 6th International Conference on Computer Vision Systems. Santorini, Greece:Springer, 2008. 66-75
[7]
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. Heraklion, Greece:Springer, 2010. 366-379
[8]
Hou X D, Zhang L Q. Saliency detection:a spectral residual approach. In:Proceedings of the 2007 IEEE International Conference on Computer Vision and Pattern Recognition. Minneapoils, USA:IEEE, 2007. 1-8
[9]
Achanta R, Hemami S, Estrada F, Süsstrunk S. Frequency-tuned salient region detection. In:Proceedings of the 2009 IEEE International Conference on Computer Vision and Pattern Recognition. Miami, USA:IEEE, 2009. 1597-1604
[10]
Cheng M M, Zhang G X, Mitra N J, Huang X, Hu S M. Global contrast based salient region detection. In:Proceedings of the 2011 IEEE International Conference on Computer Vision and Pattern Recognition. Providence, USA:IEEE, 2011. 409-416
[11]
Cheng M M, Jonathan W, Lin W Y, Zheng S, Vineet V, Crook N. Efficient salient region detection with soft image abstraction. In:Proceedings of the 2013 IEEE International Conference on Computer Vision. Sydney, Australia:IEEE, 2013. 1529-1536
[12]
Shen X, Wu Y. A unified approach to salient object detection via low rank matrix recovery. In:Proceedings of the 2012 IEEE International Conference on Computer Vision and Pattern Recognition. Providence, USA:IEEE, 2012. 853-860
[13]
Perazzi F, Kr？henbühl P, Pritch Y, Hornung A. Saliency filters:contrast based filtering for salient region detection. In:Proceedings of the 2012 IEEE International Conference on Computer Vision and Pattern Recognition. Providence, USA:IEEE, 2012. 733-740
[14]
Achanta R, Shaji A, Smith K. SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(11):2274-2282
[15]
Margolin R, Tal A, Zelnik-Manor L. What makes a patch distinct? In:Proceedings of the 2013 IEEE International Conference on Computer Vision and Pattern Recognition. Sydney, Australia:IEEE, 2013. 1139-1146
[16]
Wei Y C, Wen F, Zhu W J, Sun J. Geodesic saliency using background priors. In:Proceedings of the 2012 European Conference on Computer Vision. Florence, Italy:Springer, 2012. 29-42
[17]
Goferman S, Zelnik-Manor L, Tal A. Content-aware saliency detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(10):1915-1926
[18]
Borji A, Sihite D N, Itti L. Salient object detection:a benchmark. In:Proceedings of the 2012 European Conference on Computer Vision. Florence, Italy:Springer, 2012. 414-429
[19]
Xie Y L, Lu H C, Yang M H. Bayesian saliency via low and mid level cues. IEEE Transactions on Image Processing, 2013, 22(5):1689-1698
[20]
Alex B, Deselaers T, Ferrari V. Measuring the objectness of image windows. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(11):2189-2202
[21]
Chang K Y, Liu T L, Chen H T, Lai S H. Fusing generic objectness and visual saliency for salient object detection. In:Proceedings of the 2011 IEEE International Conference on Computer Vision. Barcelona, Spain:IEEE, 2011. 914-921
[22]
Bao L C, Song Y B, Yang Q X, Yuan H, Wang G. Tree filtering:efficient structure-preserving smoothing with a minimum spanning tree. IEEE Transactions on Image Processing, 2014, 23(2):555-569
[23]
Vedaldi A, Soatto S. Quick shift and kernel methods for mode seeking. In:Proceedings of the 2008 European Conference on Computer Vision. Marseille, France:Springer, 2008. 705-718
[24]
Frey B J, Dueck D. Clustering by passing message between data points. Science, 2007, 315(5814):972-976
[25]
Xu D, Tang Z M, Xu W. Salient object detection based on regional contrast and relative spatial compactness. KSⅡ Transactions on Internet and Information Systems, 2013, 7(11):2737-2753
[26]
Jiang B W, Zhang L H, Lu H C, Yang C, Yang M H. Saliency detection via absorbing Markov chain. In:Proceedings of the 2013 IEEE International Conference on Computer Vision. Sydney, Australia:IEEE, 2013. 1665-1672
[27]
Jiang H Z, Wang J D, Yuan Z J, Liu T, Zheng N N, Li S P. Automatic salient object segmentation based on context and shape prior. In:Proceedings of the 2011 British Machine Vision Conference. Dundee, UK:BMVA, 2011.110.1-110.12
[28]
Zhang L, Tong M H, Marks T K, Shan H, Cottrell G W. Sun:a Bayesian framework for saliency using natural statistics. Journal of Vision, 2008, 8(7):32.1-32. 20
[29]
Harel J, Koch C, Perona P. Graph-based visual saliency. In:Proceedings of the 12th Conference on Neural Information Processing Systems. Vancouver, Canada:MIT, 2007. 545-552
[30]
Zhai Y, Shah M. Visual attention detection in video sequences using spatiotemporal cues. In:Proceedings of the 14th ACM International Conference on Multimedia. Santa Barbara, USA:ACM, 2006. 815-824
[31]
Ma Ru-Ning, Tu Xiao-Po, Ding Jun-Di, Yang Jing-Yu. To evaluate salience map towards popping out visual objects. Acta Automatica Sinica, 2012, 38(5):870-876(马儒宁, 涂小坡, 丁军娣, 杨静宇. 视觉显著性凸显目标的评价. 自动化学报, 2012, 38(5):870-876)
[32]
Li X, Li Y, Shen C H, Dick A, Van Den Hengel A. Contextual hypergraph modelling for salient object detection. In:Proceedings of the 2013 IEEE International Conference on Computer Vision. Sydney, Australia:IEEE, 2013. 3328-3335
[33]
Guo Ying-Chun, Yuan Hao-Jie, Wu Peng. Image saliency detection based on local and regional features. Acta Automatica Sinica, 2013, 39(8):1214-1224(郭迎春, 袁浩杰, 吴鹏. 基于Local特征和Regional特征的图像显著性检测. 自动化学报, 2013, 39(8):1214-1224)
[34]
Jiang Xiao-Lian, Li Cui-Hua, Li Xiong-Zong. Saliency based tracking method for abrupt motions via two-stage sampling. Acta Automatica Sinica, 2014, 40(6):1098-1107(江晓莲, 李翠华, 李雄宗. 基于视觉显著性的两阶段采样突变目标跟踪算法. 自动化学报, 2014, 40(6):1098-1107)
[35]
Mai L, Niu Y Z, Liu F. Saliency aggregation:a data-driven approach. In:Proceedings of the 2013 IEEE International Conference on Computer Vision and Pattern Recognition. Sydney, Australia:IEEE, 2013. 1131-1138
