Monocular Dense 3D Reconstruction of a Complex Dynamic Scene from Two Perspective Frames

被引:24
|
作者
Kumar, Suryansh [1 ]
Dai, Yuchao [1 ,2 ]
Li, Hongdong [1 ,3 ]
机构
[1] Australian Natl Univ, Canberra, ACT, Australia
[2] Northwestern Polytech Univ, Xian, Shaanxi, Peoples R China
[3] Australia Ctr Robot Vis, Brisbane, Qld, Australia
基金
澳大利亚研究理事会;
关键词
D O I
10.1109/ICCV.2017.498
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes a new approach for monocular dense 3D reconstruction of a complex dynamic scene from two perspective frames. By applying superpixel over-segmentation to the image, we model a generically dynamic (hence non-rigid) scene with a piecewise planar and rigid approximation. In this way, we reduce the dynamic reconstruction problem to a "3D jigsaw puzzle" problem which takes pieces from an unorganized "soup of superpixels". We show that our method provides an effective solution to the inherent relative scale ambiguity in structure-from-motion. Since our method does not assume a template prior, or per-object segmentation, or knowledge about the rigidity of the dynamic scene, it is applicable to a wide range of scenarios. Extensive experiments on both synthetic and real monocular sequences demonstrate the superiority of our method compared with the state-of-the-art methods.
引用
收藏
页码:4659 / 4667
页数:9
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