• DocumentCode
    3088245
  • Title

    Depth estimation from monocular infrared images based on BP neural network model

  • Author

    Shaoyuan Sun ; Linna Li ; Lin Xi

  • Author_Institution
    Autom. Dept., Donghua Univ., Shanghai, China
  • fYear
    2012
  • fDate
    16-18 Dec. 2012
  • Firstpage
    237
  • Lastpage
    241
  • Abstract
    A depth estimation algorithm for monocular infrared image based on nonlinear learning model is proposed in this paper. Firstly, some infrared image features corresponding to the depth are extracted using stepwise regression and independent component analysis. Secondly, we regress and train the features and the corresponding depth map of an infrared image based on BP neural network. A nonlinear depth estimation model is obtained. We can estimate depth distribution of an infrared image using the model. The experimental results show that more accurate depth information can obtained based on the proposed model comparing the linear estimation model.
  • Keywords
    backpropagation; computer vision; feature extraction; independent component analysis; infrared imaging; neural nets; regression analysis; BP neural network model; depth distribution; independent component analysis; infrared image feature extraction; linear estimation model; monocular infrared Image; nonlinear depth estimation; nonlinear learning model; stepwise regression; Artificial neural networks; Automation; Educational institutions; BP neural network; depth estimation; infrared image; monocular depth;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision in Remote Sensing (CVRS), 2012 International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4673-1272-1
  • Type

    conf

  • DOI
    10.1109/CVRS.2012.6421267
  • Filename
    6421267