• DocumentCode
    1298476
  • Title

    Recognizing multiple overlapping objects in image: an optimal formulation

  • Author

    Li, Stan Z.

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Inst., Singapore
  • Volume
    9
  • Issue
    2
  • fYear
    2000
  • fDate
    2/1/2000 12:00:00 AM
  • Firstpage
    273
  • Lastpage
    277
  • Abstract
    A statistically optimal formulation is presented for recognizing multiple, partially occluded objects. The optimality, in terms of the maximum a posteriori (MAP) principle, is with respect to all, rather than just individual modeled objects. Various constraints are incorporated into the posterior distribution, a two-stage MAP estimation approach is proposed to reduce the computational cost
  • Keywords
    computational complexity; image recognition; maximum likelihood estimation; object recognition; MAP principle; computational cost; maximum a posteriori principle; multiple overlapping objects; optimal formulation; partially occluded objects; posterior distribution; statistically optimal formulation; two-stage MAP estimation approach; Computational efficiency; Data mining; Feature extraction; Image recognition; Layout; Markov random fields; Object recognition; Object segmentation; Statistics; Uncertainty;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/83.821741
  • Filename
    821741