Revolutionizing Video Production: An AI-Powered Cameraman Robot for Quality Content
Bara’ Fteiha, Rami Altai, Maha Yaghi, Huma Zia
- 发表年份
- 2024
- 引用次数
- 4
- 访问权限
- 开放获取
摘要
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.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002