Monocular Dense 3D Reconstruction of a Complex Dynamic Scene from Two Perspective Frames
August 15, 2017 Β· Declared Dead Β· π IEEE International Conference on Computer Vision
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Authors
Suryansh Kumar, Yuchao Dai, Hongdong Li
arXiv ID
1708.04398
Category
cs.CV: Computer Vision
Citations
73
Venue
IEEE International Conference on Computer Vision
Last Checked
5 months ago
Abstract
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.
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