The search functionality is under construction.

Author Search Result

[Author] Tongqing WANG(3hit)

1-3hit
  • Learning a Similarity Constrained Discriminative Kernel Dictionary from Concatenated Low-Rank Features for Action Recognition

    Shijian HUANG  Junyong YE  Tongqing WANG  Li JIANG  Changyuan XING  Yang LI  

     
    LETTER-Pattern Recognition

      Pubricized:
    2015/11/16
      Vol:
    E99-D No:2
      Page(s):
    541-544

    Traditional low-rank feature lose the temporal information among action sequence. To obtain the temporal information, we split an action video into multiple action subsequences and concatenate all the low-rank features of subsequences according to their time order. Then we recognize actions by learning a novel dictionary model from concatenated low-rank features. However, traditional dictionary learning models usually neglect the similarity among the coding coefficients and have bad performance in dealing with non-linearly separable data. To overcome these shortcomings, we present a novel similarity constrained discriminative kernel dictionary learning for action recognition. The effectiveness of the proposed method is verified on three benchmarks, and the experimental results show the promising results of our method for action recognition.

  • Statistics on Temporal Changes of Sparse Coding Coefficients in Spatial Pyramids for Human Action Recognition

    Yang LI  Junyong YE  Tongqing WANG  Shijian HUANG  

     
    LETTER-Pattern Recognition

      Pubricized:
    2015/06/01
      Vol:
    E98-D No:9
      Page(s):
    1711-1714

    Traditional sparse representation-based methods for human action recognition usually pool over the entire video to form the final feature representation, neglecting any spatio-temporal information of features. To employ spatio-temporal information, we present a novel histogram representation obtained by statistics on temporal changes of sparse coding coefficients frame by frame in the spatial pyramids constructed from videos. The histograms are further fed into a support vector machine with a spatial pyramid matching kernel for final action classification. We validate our method on two benchmarks, KTH and UCF Sports, and experiment results show the effectiveness of our method in human action recognition.

  • Dynamic Analysis of Uniplanar Guided-Wave Structures with Trapezoidal Conductor Profile and Microshielding Enclosure

    Tongqing WANG  Ke WU  

     
    PAPER

      Vol:
    E78-C No:8
      Page(s):
    1100-1105

    This work is concerned with a dynamic analysis of complex uniplanar guide-wave structures for MMICs at millimeter-wave frequencies. The enhanced spectral domain approach is effectively used to model such uniplanar structures with trapezoidal conducting strips involving microshielding enclosures. A wide range of line propagation and impedance characteristics is obtained for slotline and coplanar waveguide (CPW). The effect of different conductor profiles on line characteristics is discussed in detail. Results show an excellent agreement with other works. A class of dispersion-related curves are presented for design consideration.