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
Link To Document :
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