18256587. Enhanced Video Stabilization Based on Machine Learning Models simplified abstract (GOOGLE LLC)
Contents
Enhanced Video Stabilization Based on Machine Learning Models
Organization Name
Inventor(s)
Zhenmei Shi of Madison WI (US)
Wei-Sheng Lai of Sunnyvale CA (US)
Enhanced Video Stabilization Based on Machine Learning Models - A simplified explanation of the abstract
This abstract first appeared for US patent application 18256587 titled 'Enhanced Video Stabilization Based on Machine Learning Models
Simplified Explanation
The patent application describes an apparatus and methods for stabilizing video content. The method involves receiving image parameters and motion data associated with a video frame, and using a neural network to predict a stabilized version of the video frame.
- The patent application is related to video stabilization technology.
- A mobile computing device receives image parameters and motion data for a video frame.
- The received data is used to predict a stabilized version of the video frame.
- A neural network is applied to the image parameters and motion data for prediction.
- The technology aims to improve the stability of video content.
Potential applications of this technology:
- Video recording devices such as smartphones, action cameras, and drones could benefit from improved video stabilization.
- Video streaming platforms could use this technology to enhance the quality of live video streams.
- Virtual reality (VR) and augmented reality (AR) applications could provide a smoother and more immersive experience with stabilized video content.
Problems solved by this technology:
- Shaky or unstable video footage can be a common issue when recording videos, especially in situations with movement or handheld recording.
- Video stabilization technology helps to reduce motion blur and improve the overall quality of video content.
- It addresses the problem of shaky videos that can be distracting or unpleasant to watch.
Benefits of this technology:
- Improved video stabilization provides a better viewing experience for users.
- It allows for the creation of professional-looking videos without the need for expensive equipment.
- Stabilized video content can be more engaging and effective for various purposes such as entertainment, education, and marketing.
Original Abstract Submitted
Apparatus and methods related to stabilization of video content are provided. An example method includes receiving, by a mobile computing device, one or more image parameters associated with a video frame of a plurality of video frames. The method further includes receiving, from a motion sensor of the mobile computing device, motion data associated with the video frame. The method also includes predicting, by applying a neural network to the one or more image parameters and the motion data, a stabilized version of the video frame.
