18286560. VIDEO TRANSMISSION SYSTEM, VIDEO TRANSMISSION METHOD, AND VIDEO RECEPTION DEVICE simplified abstract (Mitsubishi Electric Corporation)

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VIDEO TRANSMISSION SYSTEM, VIDEO TRANSMISSION METHOD, AND VIDEO RECEPTION DEVICE

Organization Name

Mitsubishi Electric Corporation

Inventor(s)

Shotaro Miwa of Tokyo (JP)

VIDEO TRANSMISSION SYSTEM, VIDEO TRANSMISSION METHOD, AND VIDEO RECEPTION DEVICE - A simplified explanation of the abstract

This abstract first appeared for US patent application 18286560 titled 'VIDEO TRANSMISSION SYSTEM, VIDEO TRANSMISSION METHOD, AND VIDEO RECEPTION DEVICE

Simplified Explanation

The patent application describes a video transmission system that utilizes machine learning models to predict future video data based on acquired intermediate data.

  • Video data acquiring unit acquires first video data from a camera.
  • First inference unit processes the first video data with a learning model to acquire intermediate data.
  • Data transmission unit transmits the intermediate data.
  • Data reception unit receives the transmitted intermediate data.
  • Second inference unit processes the intermediate data with a second learning model to predict second video data.

Potential Applications

This technology can be applied in surveillance systems, video streaming services, and video editing software.

Problems Solved

This technology solves the problem of predicting future video data accurately based on acquired intermediate data.

Benefits

The system allows for real-time prediction of future video content, enhancing video processing efficiency and accuracy.

Potential Commercial Applications

  • "Predictive Video Analysis System for Enhanced Surveillance"
  • "Real-time Video Prediction Software for Live Streaming Platforms"

Possible Prior Art

One possible prior art could be the use of machine learning models in video processing and analysis systems.

Unanswered Questions

How does the system handle variations in camera settings or environmental conditions that may affect the accuracy of the predictions?

The system may need to be calibrated or trained on a diverse set of data to account for different scenarios and conditions.

What is the computational cost associated with running multiple learning models simultaneously for video prediction?

The computational resources required to run multiple learning models concurrently may impact the system's performance and efficiency.


Original Abstract Submitted

A video transmission system includes: a video data acquiring unit to acquire first video data indicating a first video photographed by a camera; a first inference unit to give the first video data to a first learning model, and acquire intermediate data that is data different from the first video data from the first learning model; a data transmission unit to transmit the intermediate data; a data reception unit to receive the intermediate data transmitted from the data transmission unit; and a second inference unit to give the intermediate data to a second learning model, and acquire, from the second learning model, second video data indicating a predicted video of a second video of which a photographing time of the camera is advanced from that of the first video by a transmission time of the intermediate data from the data transmission unit to the data reception unit or more.