Block and Group Regularized Sparse Modeling for Dictionary Learning

被引:33
作者
Chi, Yu-Tseh [1 ]
Ali, Mohsen [1 ]
Rajwade, Ajit [2 ]
Ho, Jeffrey [1 ]
机构
[1] Univ Florida, Gainesville, FL 32610 USA
[2] Dhirubhai Ambani Inst Informat & Commun Technol, Gandhinagar, India
来源
2013 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) | 2013年
关键词
RECOGNITION;
D O I
10.1109/CVPR.2013.55
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes a dictionary learning framework that combines the proposed block/group (BGSC) or reconstructed block/group (R-BGSC) sparse coding schemes with the novel Intra-block Coherence Suppression Dictionary Learning (ICS-DL) algorithm. An important and distinguishing feature of the proposed framework is that all dictionary blocks are trained simultaneously with respect to each data group while the intra-block coherence being explicitly minimized as an important objective. We provide both empirical evidence and heuristic support for this feature that can be considered as a direct consequence of incorporating both the group structure for the input data and the block structure for the dictionary in the learning process. The optimization problems for both the dictionary learning and sparse coding can be solved efficiently using block-gradient descent, and the details of the optimization algorithms are presented. We evaluate the proposed methods using well-known datasets, and favorable comparisons with state-of-the-art dictionary learning methods demonstrate the viability and validity of the proposed framework.
引用
收藏
页码:377 / 382
页数:6
相关论文
共 18 条
  • [1] [Anonymous], 2006, Journal of the Royal Statistical Society, Series B
  • [2] Bengio S., 2009, Advances in Neural Information Processing Systems, V22, P82
  • [3] LIBSVM: A Library for Support Vector Machines
    Chang, Chih-Chung
    Lin, Chih-Jen
    [J]. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2011, 2 (03)
  • [4] AN EM-ALGORITHM APPROACH FOR THE DESIGN OF ORTHONORMAL BASES ADAPTED TO SPARSE REPRESENTATIONS
    Dremeau, A.
    Herzet, C.
    [J]. 2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2010, : 2046 - 2049
  • [5] Elad M, 2010, SPARSE AND REDUNDANT REPRESENTATIONS, P3, DOI 10.1007/978-1-4419-7011-4_1
  • [6] Block-Sparse Signals: Uncertainty Relations and Efficient Recovery
    Eldar, Yonina C.
    Kuppinger, Patrick
    Boelcskei, Helmut
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2010, 58 (06) : 3042 - 3054
  • [7] Elhamifar E., 2011, 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), P1873, DOI 10.1109/CVPR.2011.5995664
  • [8] ELHAMIFAR E, 2012, SIGNAL PROCESS IEEE, P1
  • [9] Haasdonk B, 2002, INT C PATT RECOG, P864, DOI 10.1109/ICPR.2002.1048439
  • [10] A DATABASE FOR HANDWRITTEN TEXT RECOGNITION RESEARCH
    HULL, JJ
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1994, 16 (05) : 550 - 554