Nvidia corporation (20240114180). FRAME SELECTION FOR STREAMING APPLICATIONS simplified abstract
FRAME SELECTION FOR STREAMING APPLICATIONS
Organization Name
Inventor(s)
Aurobinda Maharana of Chinchwad (IN)
Vignesh Ungrapalli of Udupi (IN)
Ming-Yu Liu of San Jose CA (US)
FRAME SELECTION FOR STREAMING APPLICATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240114180 titled 'FRAME SELECTION FOR STREAMING APPLICATIONS
Simplified Explanation
The patent application addresses reference frame selection in video streaming applications by using processing units to replace a first set of frames with a second set of frames, based on an indication within the encoded video stream that the second set includes a non-blurred frame (NBF).
- The innovation involves using processing units to dynamically replace frames in a video stream based on the presence of a non-blurred frame.
- The system utilizes a cache to store frames and efficiently switch them out during video streaming.
- The indication of a non-blurred frame triggers the replacement process, ensuring better quality frames are displayed to the viewer.
Potential Applications
This technology could be applied in:
- Video streaming services
- Video conferencing platforms
- Security camera systems
Problems Solved
This technology solves issues related to:
- Improving video quality during streaming
- Enhancing user experience by reducing blurred frames
- Optimizing frame selection for better visual output
Benefits
The benefits of this technology include:
- Enhanced video quality
- Reduced blurriness in video streams
- Improved user satisfaction and engagement
Potential Commercial Applications
Commercial applications of this technology could be seen in:
- Media streaming companies
- Surveillance system providers
- Video communication software developers
Possible Prior Art
One possible prior art could be the use of caching mechanisms in video streaming applications to optimize frame delivery and quality.
Unanswered Questions
How does this technology impact bandwidth usage in video streaming applications?
This article does not delve into the potential effects on bandwidth consumption with the implementation of this technology. It would be interesting to explore whether the dynamic frame replacement has any impact on data usage.
What are the computational requirements for implementing this system in real-time video streaming applications?
The article does not provide details on the computational resources needed to execute this frame replacement process. Understanding the computational demands of this technology could be crucial for its practical implementation.
Original Abstract Submitted
systems and methods herein address reference frame selection in video streaming applications using one or more processing units to replace, during receipt of an encoded video stream, a first set of frames stored in a cache with a second set of frames based at least in part on an indication within the encoded video stream that the second set of frames includes a non-blurred frame (nbf).