Revolutionizing Video Production: An AI-Powered Cameraman Robot for Quality Content
| Autor: | Bara Fteiha, Rami Altai, Maha Yaghi, Huma Zia |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Engineering Proceedings, Vol 60, Iss 1, p 19 (2024) |
| Druh dokumentu: | article |
| ISSN: | 20240600 2673-4591 |
| DOI: | 10.3390/engproc2024060019 |
| Popis: | In today’s world of growing user-generated content on social media, this study addresses the challenge of producing high-quality content, be it for social engagement or educational purposes. Conventionally, using a cameraman has been an effective yet expensive way to enhance video quality. In this context, our research introduces an innovative AI-driven camera robot that autonomously tracks the content creator, thereby improving video production quality. The robot uses an object detection model composed of YOLOv3 and Kalman filter algorithms to identify the content creators and create a bounding box around them within the frame. Using motion detection control, the robot adjusts its position to keep the bounding box centered in the frame, ensuring a continuous focus on the content creator. As a result, the system consistently captures excellent images through precise pan-tilt movements, promising improved visual storytelling. The initial results confirm the system’s effectiveness in content detection, camera control, and content tracking. This advancement has the potential to impact user-generated content across various domains, providing an accessible way to enhance content quality without the high costs associated with traditional cameraman services. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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