• DocumentCode
    1797352
  • Title

    A 2D to 3D conversion method based on support vector machine and image classification

  • Author

    Yu-Dong Guan ; Bo-Liang Yu ; Chun-Li Ti ; Yan Ding

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Harbin Inst. of Technol., Harbin, China
  • Volume
    1
  • fYear
    2014
  • fDate
    13-16 July 2014
  • Firstpage
    88
  • Lastpage
    93
  • Abstract
    With the development of 3D technology, converting 2D videos available into 3D videos has been an important way to gain 3D contents. In the conversion, a crucial step is how to obtain a more accurate depth map. This paper proposes a method for depth extraction based on color and geometric information of the original image. Firstly, we generate a qualitative depth map by SVM and classify image scenes into three categories. Then depending on geometric information, a geometric depth map can be generated by vanishing lines detection and gradient plane assignment. At last, we blend two depth maps to get a final depth map, which has more widely application and improves accuracy of depth better.
  • Keywords
    edge detection; gradient methods; image classification; image colour analysis; support vector machines; video signal processing; 2D to 3D conversion method; 2D videos; 3D technology; 3D videos; SVM; color information; depth extraction; geometric depth map; geometric information; gradient plane assignment; image classification; image scene classifcation; qualitative depth map; support vector machine; vanishing lines detection; Abstracts; Image classification; Support vector machines; 2D to 3D; Depth map; Image classification; SVM; Vanishing point detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2014 International Conference on
  • Conference_Location
    Lanzhou
  • ISSN
    2160-133X
  • Print_ISBN
    978-1-4799-4216-9
  • Type

    conf

  • DOI
    10.1109/ICMLC.2014.7009097
  • Filename
    7009097