• DocumentCode
    2437522
  • Title

    Primitive-based 3D structure inference from a single 2D image for insect modeling: Towards an electronic field guide for insect identification

  • Author

    Zhang, Xiaozheng ; Gao, Yongsheng ; Caelli, Terry

  • Author_Institution
    Queensland Res. Lab., Nat. ICT Australia, Brisbane, QLD, Australia
  • fYear
    2010
  • fDate
    7-10 Dec. 2010
  • Firstpage
    866
  • Lastpage
    871
  • Abstract
    3D insect models are useful to overcome viewing angle variations and self-occlusions in computer-assisted insect taxonomy for electronic field guides. The acquisition of 3D information is, however, unreliable due to the flexibility and small size of the insect bodies. This paper explores how to infer 3D insect models from a single 2D insect image, which will assist both insect description and identification. The 3D structure of the insect body is modeled from two geometric primitives, generalized cylinders and deformable ellipsoids. The primitives are fitted and warped based on both edge and medial axis constraints of the 2D image. Individualized 3D models are then built to approximate the insect structure. The proposed approach results in seemingly useful 3D insect models capable of representing the major morphological characteristics for a variety of insects with different body types. This method could be a helpful assistance for computer-assisted insect taxonomy and insect identification by entomologists and the public.
  • Keywords
    image classification; 3D insect model; computer assisted insect taxonomy; entomologist; medial axis constraint; primitive based 3D structure inference; Computational modeling; Deformable models; Ellipsoids; Insects; Solid modeling; Spline; Three dimensional displays; 3D model; 3D reconstruction; insect description; structure inference;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation Robotics & Vision (ICARCV), 2010 11th International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-7814-9
  • Type

    conf

  • DOI
    10.1109/ICARCV.2010.5707814
  • Filename
    5707814