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An Intelligent Video Editing Automate Framework using AI and Computer Vision

Authors

Mei Yi Yang1 and Yu Sun2, 1Southpointe Academy, Canada, 2California State Polytechnic University, USA

Abstract

The issue to be resolved was videos may be a difficult and time-consuming process to edit, specifically with cropping videos [4]. The solution that was implemented was a mobile application that was capable of cropping videos using a body tracking solution called MediaPipe Pose [5]. Using a landmark model that labeled the body parts of a person, the application can recognize where the person is located in the video frame by saving the minimum and maximumx- and y- coordinates. In the image array, the rows and columns not included within those coordinates are deleted, which leaves only the area with the person inside. To prove the effectiveness of the application in daily life, a survey was performed on fifteen participants. Each participant was shown the same video demonstration of the application being used, then the participants answered questions regarding how useful the application would likely be in daily life and how convenient the application would be to use. Results indicate that the general public would be willing to use the application as a long-term solution for video cropping [7].

Keywords

Video Editor, Dancing, Video Cropping, Flutter.

Full Text  Volume 12, Number 18