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A Comparative Study of Video Segmentation Techniques for Graduate Detection in Thai Graduation Ceremonies
Author(s)
Chungmarisakul, Chanasorn
Date Issued
January 1, 2025
Type
Conference Paper
Abstract
Graduation ceremonies are significant occasions usually documented on lengthy, difficult-to-navigate videos. To make more satisfaction of the video needs to remove other participants and restore clear areas into short segments focused on particular graduates. By using YOLOv8 for efficient participant segmentation and the Segment Anything Model (SAM2) for accurate tracking, this study expands on earlier research by preparing videos for inpainting. The results establish the foundation for a complete system that combines inpainting, segmentation, and detection to produce polished, customized graduation video clips.
Citation
22nd International Conference on Electrical Engineering Electronics Computer Telecommunications and Information Technology Ecti Con 2025, 2025