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http://dx.doi.org/10.9708/jksci.2020.25.05.019

Generating Augmented Lifting Player using Pose Tracking  

Choi, Jong-In (Dept. of Digital Media, Seoul Women's University)
Kim, Jong-Hyun (Dept. of Software Application, Kangnam University)
Abstract
This paper proposes a framework for creating acrobatic scenes such as soccer ball lifting using various users' videos. The proposed method can generate a desired result within a few seconds using a general video of user recorded with a mobile phone. The framework of this paper is largely divided into three parts. The first is to analyze the posture by receiving the user's video. To do this, the user can calculate the pose of the user by analyzing the video using a deep learning technique, and track the movement of a selected body part. The second is to analyze the movement trajectory of the selected body part and calculate the location and time of hitting the object. Finally, the trajectory of the object is generated using the analyzed hitting information. Then, a natural object lifting scenes synchronized with the input user's video can be generated. Physical-based optimization was used to generate a realistic moving object. Using the method of this paper, we can produce various augmented reality applications.
Keywords
Augmented Reality; Artificial Intelligence; Deep Neural Networks; Posture Tracking; Video Synthesis;
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