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图像/视觉显著性检测技术发展情况梳理–计算机视觉专题

2017年12月12日 ⁄ 综合 ⁄ 共 3818字 ⁄ 字号 评论关闭

1. 早期C. Koch的研究工作.
C. Koch& S. Ullman . Shifts in selective visual attention: Towards the underlying neural circuitry. Human Neurobiology, 4(4):219-227, 1985.
C. Koch and T. Poggio. Predicting the Visual World: Silence is Golden. Nature Neuroscience, 2(1):9–10, 1999.
他们近期提出的Graph-based visual saliency效果不错.
J. Harel, C. Koch, &P. Perona. Graph-based visual saliency. Advances in Neural Information Processing Systems, 19:545-552, 2007.

2. 南加州大学iLab实验室Itti教授及其学生Siagian等的研究工作.
http://ilab.usc.edu/publications/. 主页提供iLab Neuromorphic Vision C++ Toolkit。Christian Siagian博士期间的主要工作是生物学启发的机器人视觉定位研究(Biologically Inspired Mobile Robot Vision Localization).
L. Itti, C. Koch, & E. Niebur .A model of saliency based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(11):1254-1259, 1998.
L. Itti and C. Koch. Computational Modelling of Visual Attention. Nature Reviews Neuroscience, 2(3):194–203, 2001.
L. Itti, & P. Baldi . Bayesian surprise attracts human attention. Advances in Neural Information Processing Systems, 19:547-554, 2005.
C. Siagian, L. Itti, Comparison of gist models in rapid scene categorization tasks, In: Proc. Vision Science Society Annual Meeting (VSS08), May 2008.

3. Caltech 侯晓迪博士的研究工作.
他提出的频域残差法(Spectral Residual)让人认识到数学的美。
X,Hou &L,Zhang. Saliency Detection: A spectral residual approach. IEEE Conference on Computer Vision and Pattern Recognition, 2007, pp.1-8.
Xiaodi Hou, Jonathan Harel and Christof Koch: Image Signature: Highlighting Sparse Salient Regions (PAMI 2012)
他是人大附中毕业:
http://aimit.blog.edu.cn/2009/454361.html
母校是上海交大. 同时推荐他出演的电影“The PHD Movie”:
http://movie.douban.com/subject/6855109/comments
这个BBS的回复让人忍俊不禁:
http://bbs.sjtu.edu.cn/bbstcon,board,AI,reid,1203564832.html

4. 复旦大学Chenlei Guo, Liming Zhang的工作.
他们在频域残差法(Spectral Residual)的基础上提出相位谱(Phase Spectrum)方法。
Chenlei Guo, Qi Ma, Liming Zhang: Spatio-temporal Saliency detection using phase spectrum of quaternion fourier transform. CVPR 2008
Chenlei Guo, Liming Zhang: A Novel Multiresolution Spatiotemporal Saliency Detection Model and Its Applications in Image and Video Compression. IEEE Transactions on Image Processing 19(1): 185-198 (2010)

5. 瑞士洛桑联邦理工学院EPFL的R. Achanta研究工作.
R. Achanta, F. Estrada, P. Wils, & S. Süsstrunk, Salient region detection and segmentation. International Conference on Computer Vision Systems, 2008, pp.66-75.
R. Achanta and S. Süsstrunk, “Saliency Detection for Content-aware Image Resizing,” in IEEE International Conference on
Image Processing, 2009.

R. Achanta, S. Hemami ,F. Estrada,& S. Süsstrunk, Frequency-tuned salient region detection. IEEE International Conference on Computer Vision and Pattern Recognition, 2009, pp.1597-1604.
R. Achanta and S. Süsstrunk, Saliency Detection using Maximum Symmetric Surround, ICIP, 2010.

6. 西安交通大学Tie Liu的工作:

Tie Liu, Jian Sun, Nan-Ning Zheng, Xiaoou Tang and Heung-Yeung Shum. Learning to Detect A Salient Object. In Proc. IEEE Cont. on Computer Vision and pattern Recognition (CVPR), 2007.
Tie Liu, et. al. , Video Attention: Learning to Detect A Salient Object Sequence, ICPR 2008.

7. 瑞典KIT的Boris Schauerte相关研究工作:
B. Schauerte, R. Stiefelhagen, "Predicting Human Gaze using Quaternion DCT Image Signature Saliency and Face Detection". In Proc. 12th IEEE Workshop on the Applications of Computer Vision (WACV), 2012. (Best Student Paper Award)
B. Schauerte, R. Stiefelhagen, "Quaternion-based Spectral Saliency Detection for Eye Fixation Prediction". In Proc. 12th European Conference on Computer Vision (ECCV),  2012.

其他的一些工作:

S. Goferman, L. Zelnik-Manor &A. Talr. Context-aware saliency detection. Conference on Computer Vision and Pattern Recognition, 2010, pp. 9-16.
Xiaohui Shen and Ying Wu, "A Unified Approach to Salient Object Detection via Low Rank Matrix Recovery", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR)(Oral), 2012.

国内的一些其他研究进展:
1. 清华大学可视媒体研究中心的工作,CVPR 2011.
http://vm.973program.org/EvolvementDetail.aspx?id=1
2. 南京航空航天大学马儒宁教授研究组的研究工作.
http://science.nuaa.edu.cn/vcrg/
3. 武汉大学计算机学院何发智教授的工作.
"一种随机的视觉显著性检测算法".
4. 国防科技大学杨俊博士的工作,2007.
博士论文“图像数据的视觉显著性检测技术及其应用”.
5.西工大一些工作, 2012.
http://www.ejournal.org.cn/CN/abstract/abstract6797.shtml#

文章转自于「视觉计算研究论坛」:http://www.sigvc.org/bbs/forum.php?mod=viewthread&tid=724&reltid=759&pre_thread_id=0&pre_pos=2&ext=

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