Creating Deep Learning-based Acrobatic Videos Using Imitation Videos

• Jong In Choi,
• Sang Hun Nam,

Vol. 15, No. 2, February 28, 2021
10.3837/tiis.2021.02.018, Download Paper (Free):

• Augmented Reality
• Artificial intelligence
• Pose Tracking
• Motion Analysis
• Physics Optimization

Abstract

This paper proposes an augmented reality technique to generate acrobatic scenes from hitting motion videos. After a user shoots a motion that mimics hitting an object with hands or feet, their pose is analyzed using motion tracking with deep learning to track hand or foot movement while hitting the object. Hitting position and time are then extracted to generate the object’s moving trajectory using physics optimization and synchronized with the video. The proposed method can create videos for hitting objects with feet, e.g. soccer ball lifting; fists, e.g. tap ball, etc. and is suitable for augmented reality applications to include virtual objects.

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