JOURNAL ARTICLE

Dense Rigid Reconstruction from Unstructured Discontinuous Video

Abstract

Although 3D reconstruction from a monocular video has been an active area of research for a long time, and the resulting models offer great realism and accuracy, strong conditions must be typically met when capturing the video to make this possible. This prevents general reconstruction of moving objects in dynamic, uncontrolled scenes. In this paper, we address this issue. We present a novel algorithm for modelling 3D shapes from unstructured, unconstrained discontinuous footage. The technique is robust against distractors in the scene, background clutter and even shot cuts. We show reconstructed models of objects, which could not be modelled by conventional Structure from Motion methods without additional input. Finally, we present results of our reconstruction in the presence of shot cuts, showing the strength of our technique at modelling from existing footage.

Keywords:
Computer science Computer vision Clutter Artificial intelligence Shot (pellet) Monocular Iterative reconstruction 3D reconstruction One shot Structure from motion Computer graphics (images) Motion (physics) Radar Engineering

Metrics

3
Cited By
0.63
FWCI (Field Weighted Citation Impact)
30
Refs
0.77
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
Optical measurement and interference techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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