• DocumentCode
    3116162
  • Title

    A Novel Algorithm for Moving Objects Recognition Based on Sparse Bayesian Classification

  • Author

    Changhua, Lu ; Ningning, Chang ; Rui, Fang ; Chun, Liu

  • Author_Institution
    Sch. of Comput. & Inf., Hefei Univ. of Technol., Hefei
  • fYear
    2006
  • fDate
    6-8 Sept. 2006
  • Firstpage
    135
  • Lastpage
    139
  • Abstract
    This paper deals with the problem of moving objects recognition using Bayesian method. A novel algorithm based on sparse Bayesian classification for the recognition of moving objects is proposed. This approach takes full advantage of sparse Bayesian in solving classification problems. It uses fewer kernel functions in order to reduce the complexity of the computation and resolves the over-fitting problem in recognition system. The experimental results show that this approach distinctly outperforms other classification approaches on this issue. The veracity and velocity are also satisfactory.
  • Keywords
    Bayes methods; computational complexity; image classification; image motion analysis; object recognition; computation complexity reduction; kernel function; moving object recognition; sparse Bayesian classification; Automatic control; Bayesian methods; Control systems; Feature extraction; Image recognition; Kernel; Lighting; Object recognition; Support vector machine classification; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning for Signal Processing, 2006. Proceedings of the 2006 16th IEEE Signal Processing Society Workshop on
  • Conference_Location
    Arlington, VA
  • ISSN
    1551-2541
  • Print_ISBN
    1-4244-0656-0
  • Electronic_ISBN
    1551-2541
  • Type

    conf

  • DOI
    10.1109/MLSP.2006.275536
  • Filename
    4053635