液晶与显示, 2016, 31 (1): 117, 网络出版: 2016-03-22   

基于区域特征融合的RGBD显著目标检测

RGBD salient object detection based on regional feature integration
作者单位
武汉科技大学 信息科学与工程学院, 湖北 武汉 430081
引用该论文

杜杰, 吴谨, 朱磊. 基于区域特征融合的RGBD显著目标检测[J]. 液晶与显示, 2016, 31(1): 117.

DU Jie, WU Jin, ZHU Lei. RGBD salient object detection based on regional feature integration[J]. Chinese Journal of Liquid Crystals and Displays, 2016, 31(1): 117.

参考文献

[1] 张辉, 王耀南, 周博文, 等.医药大输液可见异物自动视觉检测方法及系统研究[J].电子测量与仪器学报, 2010, 24(2): 125-130.

    ZHANG H, WANG Y N,ZHOU B W, et al. Research on automatic visual inspection method and system for foreign substances in medicine transfusion liquid[J]. Journal of Electronic Measurement and Instrument,2010,24(2): 125-130.(in Chinese)

[2] 张新龙, 汪荣贵, 张璇, 等. 基于视觉区域划分的雾天图像清晰化方法[J].电子测量与仪器学报, 2010,24(2): 125-130.

    ZHANG X L, WANG G R, ZHANG X, et al. Foggy image enhancement based on regions of human visual[J]. Journal of Electronic Measurement and Instrument, 2010,24(2): 125-130.(in Chinese)

[3] Itti L, Koch C, Niebu E, et al. A model of saliency-based visual attention for rapid scene analysis[J]. IEEE TPAMI, 1998,20(11): 1254-1259.

[4] Cheng M M, Zhang G X, Mitra N J, et al. Global contrast based salient region detection[C]. CVPR, 2011: 409-416.

[5] Perazzi F, Krahenuhl P, Pritch Y, et al.Saliency filters: Contrast based filtering for salient region detection[C]. CVPR, 2012: 733-740.

[6] LIU G C, LIN Z C, TANG X O, et al. Unsupervised object segmentation with a hybrid graph model[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2010,32(5): 910-924.

[7] JIANG H Z, WANG J D, YUAN Z Y, et al. Salient object detection: A discriminative regional feature integration approach[C]. IEEE Conference on CVPR, 2013: 208-209.

[8] ZHANGY, JIANG G, YU M, et al. Stereoscopic visual attention model for 3d video[C]. Proc.16th Int. Conf. Adv. Multimedia Model., 2010: 314-324.

[9] CHAMARET C, GODEFFROY S, LOPEZ P, et al. Adaptive 3D rendering based on region-of-interest[C]. Proc. SPIE, Stereo-scopic Displays and Application XXI, 2010: 75240V.

[10] LANG C, NGUYEN T V, KATTI H, et al. Depth matters: Influence of depth cues on visual saliency[C]. ECCV, 2012: 101-115.

[11] CIPTADI A, HERMANS T, REHG J M, et al. An in depth view of saliency[C]. BMVC, 2013: 1-11.

[12] FELZENSZWALB P F, HUTTENLOCHER D P. Efficient graph-based image segmentation[J]. International Journal of Computer Vision, 2004,59(2): 167-184.

[13] BREIMAN L, FRIEDMAN J, STONE C J, et al. Classification and regression trees[M]. NY, USA: Chapman and Hall, 1984.

[14] LIU T, YUAN Z, SUN J, et al. Learning to detect a salient object[J]. IEEE Trans. Pattern Anal. Mach. Intell, 2011,33(2): 353-367.

[15] PENG H W, LI B, XIONG W H, et al. RGBD salient object detection: A benchmark and algorithms[C]. ECCV, 2014: 92-109.

[16] YANG C, ZHANG L H, LU H H ,et al. Saliency detection via graph-based manifold ranking[C]. Computer Vision and Pattern Recognition, 2013: 3166-3173.

[17] YAN Q, XU L, SHI J P, et al. Hierarchical saliency detection[C]. IEEE Conference on CVPR, 2013: 1155-1162.

[18] WONG A, FERGANI K, ZELEK J S, et al. Statistical textural distinctiveness for salient region detection in nature images[C]. IEEE Conference on CVPR,2013: 979-986.

[19] WEI Y, WEN F, ZHU W, et al. Geodesic saliency using background priors[C]. ECCV, 2012: 29-42.

[20] MANCAS M, GOSSELIN B, DUTOIT T. RARE: A new bottom-up saliency model[C]. IEEE International Conference on Image Processing (ICIP), 2012: 641-644.

杜杰, 吴谨, 朱磊. 基于区域特征融合的RGBD显著目标检测[J]. 液晶与显示, 2016, 31(1): 117. DU Jie, WU Jin, ZHU Lei. RGBD salient object detection based on regional feature integration[J]. Chinese Journal of Liquid Crystals and Displays, 2016, 31(1): 117.

本文已被 6 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!