您的位置:首页 > 理论基础

超像素分割技术发展情况梳理(Superpixel Segmentation)--计算机视觉专题3

2013-05-12 23:14 489 查看
超像素分割技术发展情况梳理(Superpixel Segmentation)

Sason@CSDN

当前更新日期:2013.05.12.

一. 基于图论的方法(Graph-based algorithms):

1. Normalized cuts, 2000.

Jianbo Shi and Jitendra Malik. Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 22(8):888–905, 2000.

T. Cour, F. Benezit, and J. Shi. Spectral segmentation with multiscale graph decomposition. In IEEE Computer Vision and Pattern Recognition (CVPR) 2005, 2005.

2. Graph-based segmentation, 2004.

Pedro Felzenszwalb and Daniel Huttenlocher. Efficient graph-basedimage segmentation. International Journal of Computer Vision (IJCV),59(2):167–181, September 2004.

3. Graph cuts method, 2008.

Alastair Moore, Simon Prince, Jonathan Warrell, Umar Mohammed, andGraham Jones. Superpixel Lattices. IEEE Computer Vision and PatternRecognition (CVPR), 2008.

4. GCa10 and GCb10, 2010.

O. Veksler, Y. Boykov, and P. Mehrani. Superpixels and supervoxels in an energy optimization framework. In European Conference on Computer Vision (ECCV), 2010.

5. Entropy Rate Superpixel Segmentation, 2011.


Ming-Yu Liu, Tuzel, O., Ramalingam, S. , Chellappa, R., Entropy Rate Superpixel Segmentation, CVPR,2011.

二. 基于梯度下降的方法(Gradient-ascent-based algorithms):

1. Watershed,1991.

Luc Vincent and Pierre Soille. Watersheds in digital spaces: An efficient algorithm based on immersion simulations. IEEE Transactions on Pattern Analalysis and Machine Intelligence, 13(6):583–598, 1991.

2. Mean Shift, 2002.


D. Comaniciu and P. Meer. Mean shift: a robust approach toward featurespace analysis. IEEE Transactions on Pattern Analysis and MachineIntelligence, 24(5):603–619, May 2002.

3. Quick Shift, 2008

A. Vedaldi and S. Soatto. Quick shift and kernel methods for mode seeking. In European Conference on Computer Vision (ECCV), 2008.

4. Turbopixel, 2009.

A. Levinshtein, A. Stere, K. Kutulakos, D. Fleet, S. Dickinson, and K. Siddiqi. Turbopixels: Fast superpixels using geometric flows. IEEETransactions on Pattern Analysis and Machine Intelligence (PAMI),2009.




自然图像抠图/视频抠像技术发展情况梳理(image matting, alpha matting, video matting)--计算机视觉专题1
http://blog.csdn.net/anshan1984/article/details/8581225
图像/视觉显著性检测技术发展情况梳理(Saliency Detection、Visual Attention)--计算机视觉专题2 http://blog.csdn.net/anshan1984/article/details/8657176
超像素分割技术发展情况梳理(Superpixel Segmentation)--计算机视觉专题3 http://blog.csdn.net/anshan1984/article/details/8918167
欢迎来到我的CSDN博客:http://blog.csdn.net/anshan1984/


内容来自用户分享和网络整理,不保证内容的准确性,如有侵权内容,可联系管理员处理 点击这里给我发消息
标签: 
相关文章推荐