全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于局部保持的核稀疏表示字典学习

DOI: 10.3724/SP.J.1004.2014.02295, PP. 2295-2305

Keywords: 字典学习,稀疏表示,核空间,局部保持

Full-Text   Cite this paper   Add to My Lib

Abstract:

?为了利用核技巧提高分类性能,在局部保持的稀疏表示字典学习的基础上,提出了两种核化的稀疏表示字典学习方法.首先,原始训练数据被投影到高维核空间,进行基于局部保持的核稀疏表示字典学习;其次,在稀疏系数上强加核局部保持约束,进行基于核局部保持的核稀疏表示字典学习.实验结果表明,该方法的分类识别结果优于其他方法.

References

[1]  Wright J, Yang A Y, Ganesh A, Sastry S S. Robust face recognition via sparse representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(2): 210-227
[2]  Aharon M, Elad M, Bruckstein M A. The K-SVD: an algorithm for designing of overcomplete dictionaries for sparse representation. IEEE Transactions on Signal Processing, 2006, 54(11): 4311-4322
[3]  He X F, Niyogi P. Locality preserving projections. Advances in Neural Information Processing Systems. Cambridge: MIT Press, 2003. 152-160
[4]  Mike S, Ratsch G, Scholkopf B, Weston J, Muller R K. Fisher discriminant analysis with kernels. In: Proceedings of the 1999 IEEE Signal Processing Society Workshop. Madison, WI: IEEE, 1999. 41-48
[5]  Lu J W, Plataniotis K N, Venetsanopoulos A N. Face recognition using kernel direct discriminant analysis algorithms. IEEE Transactions on Neural Networks, 2003, 14(1): 117-126
[6]  Zhou Y, Liu K, Carrillo R E. Kernel-based sparse representation for gesture recognition. Pattern Recognition, 2013, 46(12): 3208-3222
[7]  Rosasco L, Verri A, Santoro M. Iterative projection methods for structured sparsity regularization [Online], available: http://hdl.handle.net/1721.1/49428, January 9, 2014
[8]  Wang Z Q, Qian X. Document classification algorithm using kernel LPP. In: Proceedings of 2009 International Conference on Computational Intelligence and Natural Computing. Wuhan, China: IEEE, 2009, 2: 100-102mm
[9]  Nene S A, Nayar S K, Murase H. Columbia Object Image Library (COIL-20). Technical Report CUCS-005-96, February 1996 [Online], available: http://www.cs.columbia.edu/CAVE/software/softlib/coil-20.php, January 9, 2014mm
[10]  Naseem I, Togneri R, Bennamoun M. Linear regression for face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(11): 2106-2112mm
[11]  Zhang D, Yang M, Feng X. Sparse representation or collaborative representation: which helps face recognition? In: Proceedings of 2011 IEEE International Conference on Computer Vision (ICCV). Barcelona, Spain: IEEE, 2011. 471-478
[12]  Liu Fang, Wu Jiao, Yang Shu-Yuan, Jiao Li-Cheng. Research advances on structured compressive sensing. Acta Automatica Sinica, 2013, 39(12): 1980-1995(刘芳, 武娇, 杨淑媛, 焦李成. 结构化压缩感知研究进展. 自动化学报, 2013, 39(12): 1980-1995)
[13]  Hu Zheng-Ping, Song Shu-Fen. Robust image recognition algorithm of maximum likelihood estimation sparse representation based on class-related neighbors subspace. Acta Automatica Sinica, 2012, 38(9): 1420-1427(胡正平, 宋淑芬. 基于类别相关近邻子空间的最大似然稀疏表示鲁棒图像识别算法. 自动化学报, 2012, 38(9): 1420-1427)
[14]  Ma Xiao-Hu, Tan Yan-Qi. Face recognition based on discriminant sparsity preserving embedding. Acta Automatica Sinica, 2014, 40(1): 73-82(马小虎, 谭延琪. 基于鉴别稀疏保持嵌入的人脸识别算法. 自动化学报, 2014, 40(1): 73-82)
[15]  Engan K, Aase S O, Hakon H J. Method of optimal directions for frame design. In: Proceedings of Acoustics, Speech, and Signal Processing. Arizona, USA: IEEE, 1999, 5: 2443-2446
[16]  Yang M, Zhang L, Feng X. Fisher discrimination dictionary learning for sparse representation. In: Proceedings of 2011 IEEE International Conference on Computer Vision(ICCV). Barcelona, Spain: IEEE, 2011. 543-550
[17]  Chen Si-Bao, Zhao Ling, Luo Bin. Dictionary learning via locality preserving for sparse representation. Journal of South China university of Technology (Natural Science Edition), 2014, 42(1): 142-146(陈思宝, 赵令, 罗斌. 局部保持的稀疏表示字典学习. 华南理工大学学报(自然科学版), 2014, 42(1): 142-146)
[18]  Scholkopf B, Smola A, Muller K R. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 1998, 10(5): 1299-1319
[19]  Gao S, Tsang I, Chia L T. Sparse representation with kernels. IEEE Transactions on Image Processing, 2013, 22(2): 423-434
[20]  Yin J, Liu Z H, Jin Z, Yang W K. Kernel sparse representation based classification. Neurocomputing, 2012, 77(1): 120-128
[21]  He X F, Yan S C, Hu Y X, Niyogi P. Face recognition using laplacianfaces. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(3): 328-340
[22]  Yang M, Zhang L, Yang J. Metaface learning for sparse representation based face recognition. In: Proceedings of the 17th IEEE International Conference on Image Processing. Hong Kong, China: IEEE, 2010. 1601-1604mm
[23]  Huang R B, Su C M, Lang F N, Du M H. Kernel discriminant locality preserving projections for human face recognition. Journal of Information and Computational Science, 2010, 7(4): 925-931mm
[24]  Martinez A, Benavente R. The AR Face Database. The Ohio State University CVC Tech. Report No. 24, June, 1998

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133