arxiv:1806.00890

Soccer on Your Tabletop

Published on Jun 3, 2018

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Abstract

The system uses a CNN to estimate depth maps from monocular soccer videos, enabling 3D reconstruction and interactive rendering.

AI-generated summary

We present a system that transforms a monocular video of a soccer game into a moving 3D reconstruction, in which the players and field can be rendered interactively with a 3D viewer or through an Augmented Reality device. At the heart of our paper is an approach to estimate the depth map of each player, using a CNN that is trained on 3D player data extracted from soccer video games. We compare with state of the art body pose and depth estimation techniques, and show results on both synthetic ground truth benchmarks, and real YouTube soccer footage.

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