| [1] | 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 doi: 10.1109/TPAMI.2012.89 |
| [2] | Wang Wen-Guan, Shen Jian-Bing, Shao Ling, Porikli Fatih. Correspondence driven saliency transfer. IEEE Transaction on Image Processing, 2016, 25(11): 5025-5034 doi: 10.1109/TIP.2016.2601784 |
| [3] | 丁正虎, 余映, 王斌, 张立明.选择性视觉注意机制下的多光谱图像舰船检测.计算机辅助设计与图形学学报, 2011, 23(3): 419-425 http://d.old.wanfangdata.com.cn/Periodical/jsjfzsjytxxxb201103007 Ding Zheng-Hu, Yu Ying, Wang Bin, Zhang Li-Ming. Visual attention-based ship detection in multispectral imagery. Journal of Computer-Aided Design & Computer Graphics, 2011, 23(3): 419-425 http://d.old.wanfangdata.com.cn/Periodical/jsjfzsjytxxxb201103007 |
| [4] | Gao D S, Han S Y, Vasconcelos N. Discriminant saliency, the detection of suspicious coincidences, and applications to visual recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(6): 989-1005 doi: 10.1109/TPAMI.2009.27 |
| [5] | Jian M W, Dong J Y, Ma J. Image retrieval using wavelet-based salient regions. The Imaging Science Journal, 2011, 59(4): 219-231 doi: 10.1179/136821910X12867873897355 |
| [6] | 王向阳, 杨红颖, 郑宏亮, 吴俊峰.基于视觉权值的分块颜色直方图图像检索算法.自动化学报, 2010, 36(10): 1489-1492 doi: 10.3724/SP.J.1004.2010.01489 Wang Xiang-Yang, Yang Hong-Ying, Zheng Hong-Liang, Wu Jun-Feng. A color block-histogram image retrieval based on visual weight. Acta Automatica Sinica, 2010, 36(10): 1489-1492 doi: 10.3724/SP.J.1004.2010.01489 |
| [7] | 冯欣, 杨丹, 张凌.基于视觉注意力变化的网络丢包视频质量评估.自动化学报, 2011, 37(11): 1322-1331 doi: 10.3724/SP.J.1004.2011.01322 Feng Xin, Yang Dan, Zhang Ling. Saliency variation based quality assessment for packet-loss-impaired videos. Acta Automatica Sinica, 2011, 37(11): 1322-1331 doi: 10.3724/SP.J.1004.2011.01322 |
| [8] | Gupta R, Chaudhury S. A scheme for attentional video compression. In: Proceedings of the 4th International Conference on Pattern Recognition and Machine Intelligence. Moscow, Russia: IEEE, 2011. 458-465 |
| [9] | Guo C L, Zhang L M. A novel multiresolution spatiotemporal saliency detection model and its applications in image and video compression. IEEE Transactions on Image Processing, 2010, 19(1): 185-198 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=560c7c523a5fae193c072cc702070cd8 |
| [10] | 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, Belgium: IEEE, 2011. 2469-2472 |
| [11] | 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 doi: 10.3724/SP.J.1004.2014.01098 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 doi: 10.3724/SP.J.1004.2014.01098 |
| [12] | 黎万义, 王鹏, 乔红.引入视觉注意机制的目标跟踪方法综述.自动化学报, 2014, 40(4): 561-576 doi: 10.3724/SP.J.1004.2014.00561 Li Wan-Yi, Wang Peng, Qiao Hong. A survey of visual attention based methods for object tracking. Acta Automatica Sinica, 2014, 40(4): 561-576 doi: 10.3724/SP.J.1004.2014.00561 |
| [13] | Le Callet P, Niebur E. Visual attention and applications in multimedia technologies. Proceedings of the IEEE, 2013, 101(9): 2058-2067 doi: 10.1109/JPROC.2013.2265801 |
| [14] | Wang J L, Fang Y M, Narwaria M, Lin W S, Le Callet P. Stereoscopic image retargeting based on 3D saliency detection, In: Proceedings of 2014 International Conference on Acoustics, Speech, and Signal Processing. Florence, Italy: IEEE, 2014. 669-673 |
| [15] | Kim H, Lee S, Bovik A C. Saliency prediction on stereoscopic videos. IEEE Transactions on Image Processing, 2014, 23(4): 1476-1490 doi: 10.1109/TIP.2014.2303640 |
| [16] | Zhang Y, Jiang G Y, Yu M, Chen K. Stereoscopic visual attention model for 3D video. In: Proceedings of the 16th International Conference on Multimedia Modeling. Chongqing, China: Springer, 2010. 314-324 |
| [17] | Uherčík M, Kybic J, Zhao Y, Cachard C, Liebgott H. Line filtering for surgical tool localization in 3D ultrasound images. Computers in Biology and Medicine, 2013, 43(12): 2036-2045 doi: 10.1016/j.compbiomed.2013.09.020 |
| [18] | Zhao Y, Cachard C, Liebgott H. Automatic needle detection and tracking in 3D ultrasound using an ROI-based RANSAC and Kalman method. Ultrasonic Imaging, 2013, 35(4): 283-306 doi: 10.1177/0161734613502004 |
| [19] | 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 doi: 10.1109/34.730558 |
| [20] | 胡正平, 孟鹏权.全局孤立性和局部同质性图表示的随机游走显著目标检测算法.自动化学报, 2011, 37(10): 1279-1284 doi: 10.3724/SP.J.1004.2011.01279 Hu Zheng-Ping, Meng Peng-Quan. Graph presentation random walk salient object detection algorithm based on global isolation and local homogeneity. Acta Automatica Sinica, 2011, 37(10): 1279-1284 doi: 10.3724/SP.J.1004.2011.01279 |
| [21] | Cheng M M, Mitra N J, Huang X L, Torr P H S, Hu S M. Global contrast based salient region detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(3): 569-582 doi: 10.1109/TPAMI.2014.2345401 |
| [22] | 唐勇, 杨林, 段亮亮.基于图像单元对比度与统计特性的显著性检测.自动化学报, 2013, 39(10): 1632-1641 doi: 10.3724/SP.J.1004.2013.01632 Tang Yong, Yang Lin, Duan Liang-Liang. Image cell based saliency detection via color contrast and distribution. Acta Automatica Sinica, 2013, 39(10): 1632-1641 doi: 10.3724/SP.J.1004.2013.01632 |
| [23] | 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 doi: 10.3724/SP.J.1004.2013.01214 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 doi: 10.3724/SP.J.1004.2013.01214 |
| [24] | 徐威, 唐振民.利用层次先验估计的显著性目标检测.自动化学报, 2015, 41(4): 799-812 doi: 10.16383/j.aas.2015.c140281 Xu Wei, Tang Zhen-Min. Exploiting hierarchical prior estimation for salient object detection. Acta Automatica Sinica, 2015, 41(4): 799-812 doi: 10.16383/j.aas.2015.c140281 |
| [25] | Shi K Y, Wang K Z, Lu J, B Lin L. PISA: pixelwise image saliency by aggregating complementary appearance contrast measures with spatial priors. In: Proceedings of 2013 IEEE Conference on Computer Vision and Pattern Recognition. Portland, OR, USA: IEEE, 2013. 2115-2122 |
| [26] | Judd T, Ehinger K, Durand F, Torralba A. Learning to predict where humans look. In: Proceedings of the 12th International Conference on Computer Vision. Kyoto, Japan: IEEE, 2009. 2106-2113 |
| [27] | Liu T, Yuan Z J, Sun J, Wang J D, Zheng N N, Tang X O, et al. Learning to detect a salient object. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(2): 353-367 doi: 10.1109/TPAMI.2010.70 |
| [28] | 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. Firenze, Italy: Springer, 2012. 29-42 |
| [29] | 钱生, 陈宗海, 林名强, 张陈斌.基于条件随机场和图像分割的显著性检测.自动化学报, 2015, 41(4): 711-724 doi: 10.16383/j.aas.2015.c140328 Qian Sheng, Chen Zong-Hai, Lin Ming-Qiang, Zhang Chen-Bin. Saliency detection based on conditional random field and image segmentation. Acta Automatica Sinica, 2015, 41(4): 711-724 doi: 10.16383/j.aas.2015.c140328 |
| [30] | Shen X H, Wu Y. A unified approach to salient object detection via low rank matrix recovery. In: Proceedings of 2012 IEEE Conference on Computer Vision and Pattern Recognition. Providence, RI, USA: IEEE, 2012. 853-860 |
| [31] | 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 2011 British Machine Vision Conference. Dundee, UK: BMVA Press, 2011. 110.1-110.12 |
| [32] | Yang C, Zhang L H, Lu H C, Ruan X, Yang M H. Saliency detection via graph-based manifold ranking. In: Proceedings of 2013 IEEE Conference on Computer Vision and Pattern Recognition. Portland, OR, USA: IEEE, 2013. 3166-3173 |
| [33] | Zhao R, Ouyang W L, Li H S, Wang X G. Saliency detection by multi-context deep learning. In: Proceedings of 2015 IEEE Conference on Computer Vision and Pattern Recognition. Boston, MA, USA: IEEE, 2015. 1265-1274 |
| [34] | Li G B, Yu Y Z. Visual saliency detection based on multiscale deep CNN features. IEEE Transactions on Image Processing, 2016, 25(11): 5012-5024 doi: 10.1109/TIP.2016.2602079 |
| [35] | Lang C Y, Nguyen T V, Katti H, Yadati K, Kankanhalli M, Yan S C. Depth matters: influence of depth cues on visual saliency. In: Proceedings of 12th European Conference on Computer Vision. Firenze, Italy: Springer, 2012. 101-115 |
| [36] | Desingh K, Krishna K M, Rajan D, Jawahar C V. Depth really matters: improving visual salient region detection with depth. In: Proceedings of 2013 British Machine Vision Conference. Bristol, England: BMVA Press, 2013. 98.1-98.11 |
| [37] | Niu Y Z, Geng Y J, Li X Q, Liu F. Leveraging stereopsis for saliency analysis. In: Proceedings of 2012 IEEE Conference on Computer Vision and Pattern Recognition. Providence, RI, USA: IEEE, 2012. 454-461 |
| [38] | Ju R, Ge L, Geng W J, Ren T W, Wu G S. Depth saliency based on anisotropic center-surround difference. In: Proceedings of 2014 IEEE International Conference on Image Processing. Pairs, France: IEEE, 2014. 1115-1119 http://www.researchgate.net/publication/282375096_Depth_saliency_based_on_anisotropic_center-surround_difference |
| [39] | Ren J Q, Gong X J, Yu L, Zhou W H, Yang M Y. Exploiting global priors for RGB-D saliency detection. In: Proceedings of 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops. Boston, MA, USA: IEEE, 2015. 25-32 http://www.researchgate.net/publication/288507923_Exploiting_global_priors_for_RGB-D_saliency_detection |
| [40] | Peng H W, Li B, Xiong W H, Hu W M, Ji R R. RGBD salient object detection: a benchmark and algorithms. In: Proceedings of 13th European Conference on Computer Vision. Zurich, Switzerland: Springer, 2014. 92-109 |
| [41] | Fang Y M, Wang J L, Narwaria M, Le Callet P, Lin W S. Saliency detection for stereoscopic images. IEEE Transactions on Image Processing, 2014, 23(6): 2625-2636 doi: 10.1109/TIP.2014.2305100 |
| [42] | Ciptadi A, Hermans T, Rehg J. An in depth view of saliency. In: Proceedings of 2013 British Machine Vision Conference. Bristol, United Kingdom: BMVA Press, 2013. 112.1-112.11 |
| [43] | Wu P L, Duan L L, Kong L F. RGB-D salient object detection via feature fusion and multi-scale enhancement. In: Proceedings of 2015 CCF Chinese Conference on Computer Vision. Xi'an, China: Springer, 2015. 359-368 doi: 10.1007/978-3-662-48570-5_35 |
| [44] | Iatsun I, Larabi M C, Fernandez-Maloigne C. Using monocular depth cues for modeling stereoscopic 3D saliency. In: Proceedings of 2014 IEEE International Conference on Acoustics, Speech and Signal Processing. Florence, Italy: IEEE, 2014. 589-593 |
| [45] | Ouerhani N, Hugli H. Computing visual attention from scene depth. In: Proceedings of the 15th International Conference on Pattern Recognition. Barcelona, Spain: IEEE, 2000. 375-378 |
| [46] | Xue H Y, Gu Y, Li Y J, Yang J. RGB-D saliency detection via mutual guided manifold ranking. In: Proceedings of 2015 IEEE International Conference on Image Processing. Quebec City, QC, Canada: IEEE, 2015. 666-670 |
| [47] | Wang J L, Da Silva M P, Le Callet P, Ricordel V. Computational model of stereoscopic 3D visual saliency. IEEE Transactions on Image Processing, 2013, 22(6): 2151-2165 doi: 10.1109/TIP.2013.2246176 |
| [48] | Iatsun I, Larabi M C, Fernandez-Maloigne C. Visual attention modeling for 3D video using neural networks. In: Proceedings of 2014 International Conference on 3D Imaging. Liege, Belglum: IEEE, 2014. 1-8 |
| [49] | Fang Y M, Lin W S, Fang Z J, Lei J J, Le Callet P, Yuan F N. Learning visual saliency for stereoscopic images. In: Proceedings of 2014 IEEE International Conference on Multimedia and Expo Workshops. Chengdu, China: IEEE, 2014. 1-6 |
| [50] | Bertasius G, Park H S, Shi J B. Exploiting egocentric object prior for 3D saliency detection. arXiv: 1511.02682, 2015. |
| [51] | Achanta R, Shaji A, Smith K, Lucchi A, Fua P, Süsstrunk S. Slic superpixels compared to state-of-the-art superpixel methods. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(11): 2274-2282 doi: 10.1109/TPAMI.2012.120 |
| [52] | Qu L Q, He S F, Zhang J W, Tian J D, Tang Y D, Yang Q X. RGBD salient object detection via deep fusion. IEEE Transactions on Image Processing, 2017, 26(5): 2274-2285 doi: 10.1109/TIP.2017.2682981 |
| [53] | Gupta S, Hoffman J, Malik J. Cross modal distillation for supervision transfer. In: Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, NV, USA: IEEE, 2016. 2827-2836 |
| [54] | Shan H H, Banerjee A, Oza N C. Discriminative mixed-membership models. In: Proceedings of the 9th IEEE International Conference on Data Mining. Miami, Florida, USA: IEEE, 2009. 466-475 |
| [55] | Wang S T, Zhou Z, Qu H B, Li B. Visual saliency detection for RGB-D images with generative model. In: Proceedings of the 13th Asian Conference on Computer Vision. Taipei, China: Springer, 2016. 20-35 |
| [56] | Rish I. An empirical study of the naive Bayes classifier. Journal of Universal Computer Science, 2001, 3(22): 41-46 |
| [57] | Blei D M, Jordan M I. Variational inference for dirichlet process mixtures. Bayesian Analysis, 2006, 1(1): 121-143 doi: 10.1214/06-BA104 |
| [58] | Sun D Q, Roth S, Black M J. Secrets of optical flow estimation and their principles. In: Proceedings of 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Francisco, CA, USA: IEEE, 2010. 2432-2439 |