17955740. FRAME SELECTION FOR STREAMING APPLICATIONS simplified abstract (NVIDIA Corporation)
Contents
- 1 FRAME SELECTION FOR STREAMING APPLICATIONS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 FRAME SELECTION FOR STREAMING APPLICATIONS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Optimizing Video Quality in Streaming Services
- 1.6 How does the system handle different types of motion in video frames?
- 1.7 What impact does the adaptive threshold have on the overall performance of the system?
- 1.8 Original Abstract Submitted
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 17955740 titled 'FRAME SELECTION FOR STREAMING APPLICATIONS
Simplified Explanation
The patent application addresses reference frame selection in video streaming applications by identifying blurred frames based on variance of motion (VoM) and adaptive thresholds.
- Explanation of the patent:
* The system uses processing units to analyze frames in a video stream. * Frames with a VoM below a certain threshold are identified as blurred frames. * The adaptive threshold is determined based on a moving average of variance of motion (MAoV) using reference frames.
Potential applications of this technology:
- This technology can be applied in video streaming services to improve video quality by identifying and filtering out blurred frames.
- It can also be used in video editing software to automatically detect and enhance blurry frames in videos.
Problems solved by this technology:
- Helps in improving the overall viewing experience by reducing the presence of blurred frames in video streams.
- Enables more efficient video processing by automatically identifying and handling blurred frames.
Benefits of this technology:
- Enhances the quality of video streams by removing or enhancing blurred frames.
- Increases the efficiency of video processing by automating the identification of blurred frames.
Potential commercial applications of this technology:
Optimizing Video Quality in Streaming Services
Possible prior art: There may be existing technologies or methods that address frame selection and quality enhancement in video streaming applications, but specific prior art is not provided in the abstract.
Unanswered questions:
How does the system handle different types of motion in video frames?
The abstract does not specify how the system distinguishes between different types of motion in frames, such as camera movement versus object motion.
What impact does the adaptive threshold have on the overall performance of the system?
The abstract mentions an adaptive threshold based on MAoV, but it does not elaborate on how this threshold affects the system's performance in identifying blurred frames.
Original Abstract Submitted
Systems and methods herein address reference frame selection in video streaming applications using one or more processing units to identify a frame of a sequence of frames as a blurred frame based at least in part on a first variance of motion (VoM) of the frame being less than or equal to an adaptive threshold that is based in part on a moving average of variance of motion (MAoV) determined using one or more reference frames.
