正在加载图片...
·950· 智能系统学报 第13卷 compression method[]].Journal of Chongqing university tion at 300fps[C]//Proceedings of IEEE conference on of posts and telecommunications:natural science edition, computer vision and pattern recognition.Columbus,OH, 2015.27(2):279-284. USA.2014:3286-3293. [2]杨林娜.安玮，林再平，等.基于空间距离改进的视觉显 [15]ZITNICK C L,DOLLaR P.Edge boxes:Locating object 著性弱小目标检测[.光学学报，2015,35(7)：0715004 proposals from edges[C]//Proceedings of European Con- YANG Linna,AN Wei,LIN Zaiping,et al.Small target ference on Computer Vision.Cham:Springer,2014: detection based on visual saliency improved by spatial dis- 391-405. tance[J].Acta optica sinica,2015.35(7):0715004. [16]ACHANTA R,SHAJI A,SMITH K,et al.SLIC super- [3]ITTI L.Automatic foveation for video compression using a pixels compared to state-of-the-art superpixel methods[J]. neurobiological model of visual attention[J].IEEE transac- IEEE transactions on pattern analysis and machine intelli- tions on image processing,2004,13(10):1304-1318. gence,2012,3411):2274-2282 [4]CHEN Tao,CHENG Mingming,TAN Ping,et al. [17]HUANG Fang,QI Jinging,LU Huchuan,et al.Salient ob- Sketch2photo:internet image montage[J].ACM transac- ject detection via multiple instance learning[J].IEEE tions on graphics,2009,28(5):1-10. transactions on image processing,2017,26(4):1911- [5]CHENG Mingming,MITRA N J,HUANG Xiaolei,et al. 1922. Global contrast based salient region detection[J].IEEE [18]PERAZZI F,KRAHENBUHL P,PRITCH Y,et al.Sali- transactions on pattern analysis and machine intelligence, ency filters:Contrast based filtering for salient region de- 2015,37(3):569-582 tection[C]//Proceedings of IEEE Conference on Com- [6]HAREL J.KOCH C.PERONA P.Graph-based visual sali- puter Vision and Pattern Recognition.Providence,RI, ency[C]//Proceedings of the 19th International Conference USA.2012:733-740. on Neural Information Processing Systems.Cambridge, [19]XI Tao.ZHAO Wei.WANG Han,et al.Salient object de- MA.USA.2007:545-552. tection with spatiotemporal background priors for [7]ERDEM E,ERDEM A.Visual saliency estimation by non- video[J].IEEE transactions on image processing,2017, linearly integrating features using region covariances[J]. 26(7:3425-3436. Journal of vision,2013,13(4):11. [20]ZHU Wangjiang,LIANG Shuang,WEI Yichen,et al.Sa- [8]MURRAY N,VANRELL M,OTAZU X,et al.Saliency liency optimization from robust background detection estimation using a non-parametric low-level vision model [Cl//Proceedings of IEEE conference on computer vision [C]//Proceedings of the 2011 IEEE Conference on Com- and pattern recognition.Columbus,OH,USA,2014: puter Vision and Pattern Recognition.Washington,DC, 2814-2821. USA,2011:433-440. [21]刘丽，匡纲要.图像纹理特征提取方法综述[】.中国图 [9]SHI Jianping,YAN Qiong,XU Li,et al.Hierarchical im- 象图形学报，2009,144)：622-635 age saliency detection on extended CSSD[J].IEEE transac- LIU li,KUANG Gangyao.Overview of image textural tions on pattern analysis and machine intelligence,2016, feature extraction methods[J].Journal of image and 38(4):717-729 graphics,2009,14(4):622-635. [10]YANG Chuan,ZHANG Lihe,LU Huchuan,et al.Sali- [22]王佐成，薛丽霞.一种新的纹理基元发现及表达方法[ ency detection via graph-based manifold ranking[C]//Pro- 重庆邮电大学学报：自然科学版，2011,23(1)：115-120 ceedings of the IEEE conference on computer vision and WANG Zuocheng,XUE Lixia.A new representation pattern recognition.Washington,DC,USA,2013:3166- method of image texton[J].Journal of Chongqing uni- 3173. versity of posts and telecommunications:natural science [11]LIU Tie,YUAN Zejian,SUN Jian,et al.Learning to de- edition.2011,23(1):115-120. tect a salient object[J].IEEE transactions on pattern ana- [23]WANG Qi,YUAN Yuan,YAN Pingkun.Visual saliency lysis and machine intelligence,2011,33(2):353-367. by selective contrast[J].IEEE transactions on circuits and [12]YANG Jimei,YANG M H.Top-down visual saliency via systems for video technology,2013,23(7):1150-1155. joint CRF and dictionary learning[C]//Proceedings of [24]HARTIGAN J A,WONG M A.Algorithm as 136:a k- Conference on Computer Vision and Pattern Recognition means clustering algorithm.Journal of the royal statist- (CVPR).Washington,DC.USA.2012:2296-2303. ical society.series c (applied statistics),1979,28(1): [13]ALEXE B,DESELAERS T.FERRARI V.Measuring the 100-108. objectness of image windows[.IEEE transactions on [25]HOU Xiaodi,ZHANG Liqing.Saliency detection:a spec- pattern analysis and machine intelligence,2012,34(11): tral residual approach[C]//Proceedings of IEEE Confer- 2189-2202. ence on Computer Vision and Pattern Recognition.Min- [14]CHENG Mingming,ZHANG Ziming,LIN Wenyan,et al. neapolis,MN,USA,2007:1-8 BING:Binarized normed gradients for objectness estima- [26]ACHANTA R,HEMAMI S,Estrada F,et al.Frequency-compression method[J]. Journal of Chongqing university of posts and telecommunications: natural science edition, 2015, 27(2): 279–284. 杨林娜, 安玮, 林再平, 等. 基于空间距离改进的视觉显 著性弱小目标检测[J]. 光学学报, 2015, 35(7): 0715004. YANG Linna, AN Wei, LIN Zaiping, et al. Small target detection based on visual saliency improved by spatial distance[J]. Acta optica sinica, 2015, 35(7): 0715004. [2] ITTI L. Automatic foveation for video compression using a neurobiological model of visual attention[J]. IEEE transactions on image processing, 2004, 13(10): 1304–1318. [3] CHEN Tao, CHENG Mingming, TAN Ping, et al. Sketch2photo: internet image montage[J]. ACM transactions on graphics, 2009, 28(5): 1–10. [4] CHENG Mingming, MITRA N J, HUANG Xiaolei, et al. Global contrast based salient region detection[J]. IEEE transactions on pattern analysis and machine intelligence, 2015, 37(3): 569–582. [5] HAREL J, KOCH C, PERONA P. Graph-based visual saliency[C]//Proceedings of the 19th International Conference on Neural Information Processing Systems. Cambridge, MA, USA, 2007: 545–552. [6] ERDEM E, ERDEM A. Visual saliency estimation by nonlinearly integrating features using region covariances[J]. Journal of vision, 2013, 13(4): 11. [7] MURRAY N, VANRELL M, OTAZU X, et al. Saliency estimation using a non-parametric low-level vision model [C]//Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition . Washington, DC, USA, 2011: 433–440. [8] SHI Jianping, YAN Qiong, XU Li, et al. Hierarchical image saliency detection on extended CSSD[J]. IEEE transactions on pattern analysis and machine intelligence, 2016, 38(4): 717–729. [9] YANG Chuan, ZHANG Lihe, LU Huchuan, et al. Saliency detection via graph-based manifold ranking[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. Washington, DC, USA, 2013: 3166– 3173. [10] LIU Tie, YUAN Zejian, SUN Jian, et al. Learning to detect a salient object[J]. IEEE transactions on pattern analysis and machine intelligence, 2011, 33(2): 353–367. [11] YANG Jimei, YANG M H. Top-down visual saliency via joint CRF and dictionary learning[C]//Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR). Washington, DC, USA, 2012: 2296–2303. [12] ALEXE B, DESELAERS T, FERRARI V. Measuring the objectness of image windows[J]. IEEE transactions on pattern analysis and machine intelligence, 2012, 34(11): 2189–2202. [13] CHENG Mingming, ZHANG Ziming, LIN Wenyan, et al. BING: Binarized normed gradients for objectness estima- [14] tion at 300fps[C]//Proceedings of IEEE conference on computer vision and pattern recognition. Columbus, OH, USA, 2014: 3286–3293. ZITNICK C L, DOLLáR P. Edge boxes: Locating object proposals from edges[C]//Proceedings of European Conference on Computer Vision. Cham: Springer, 2014: 391–405. [15] ACHANTA R, SHAJI A, SMITH K, et al. SLIC superpixels compared to state-of-the-art superpixel methods[J]. IEEE transactions on pattern analysis and machine intelligence, 2012, 34(11): 2274–2282. [16] HUANG Fang, QI Jinqing, LU Huchuan, et al. Salient object detection via multiple instance learning[J]. IEEE transactions on image processing, 2017, 26(4): 1911– 1922. [17] PERAZZI F, KRÄHENBÜHL P, PRITCH Y, et al. Saliency filters: Contrast based filtering for salient region detection[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Providence, RI, USA, 2012: 733–740. [18] XI Tao, ZHAO Wei, WANG Han, et al. Salient object detection with spatiotemporal background priors for video[J]. IEEE transactions on image processing, 2017, 26(7): 3425–3436. [19] ZHU Wangjiang, LIANG Shuang, WEI Yichen, et al. Saliency optimization from robust background detection [C]//Proceedings of IEEE conference on computer vision and pattern recognition. Columbus, OH, USA, 2014: 2814–2821. [20] 刘丽, 匡纲要. 图像纹理特征提取方法综述[J]. 中国图 象图形学报, 2009, 14(4): 622–635. LIU li, KUANG Gangyao. Overview of image textural feature extraction methods[J]. Journal of image and graphics, 2009, 14(4): 622–635. [21] 王佐成, 薛丽霞. 一种新的纹理基元发现及表达方法[J]. 重庆邮电大学学报: 自然科学版, 2011, 23(1): 115–120. WANG Zuocheng, XUE Lixia. A new representation method of image texton[J]. Journal of Chongqing university of posts and telecommunications: natural science edition, 2011, 23(1): 115–120. [22] WANG Qi, YUAN Yuan, YAN Pingkun. Visual saliency by selective contrast[J]. IEEE transactions on circuits and systems for video technology, 2013, 23(7): 1150–1155. [23] HARTIGAN J A, WONG M A. Algorithm as 136: a kmeans clustering algorithm[J]. Journal of the royal statistical society. series c (applied statistics), 1979, 28(1): 100–108. [24] HOU Xiaodi, ZHANG Liqing. Saliency detection: a spectral residual approach[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Minneapolis, MN, USA, 2007: 1–8. [25] [26] ACHANTA R, HEMAMI S, Estrada F, et al. Frequency- ·950· 智 能 系 统 学 报 第 13 卷