Dynamic Video Quality Control via Eye Tracking ROI
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Solution Overview
Problem
Existing devices struggle to render high-definition (HD) video due to bandwidth limitations, as HD video requires significantly more bandwidth than standard definition (SD) video, leading to poor video quality in scenarios where limited bandwidth is available.
Innovation Solution
A method and device that dynamically control video quality by detecting the user's eye position and predicting the next gaze point, converting SD video to HD video only on the region of interest (ROI) on the screen associated with the current and next eye position, and displaying the HD video on that ROI.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If HD video is rendered on the entire display screen, then video quality is improved, but bandwidth consumption increases significantly
Solution Approach 1:
The patent applies local quality by rendering HD video only in the region of interest (ROI) where the user is looking, while displaying SD video in other regions. This is achieved by converting SD video to HD video specifically for the ROI area based on eye position detection, thereby improving video quality where needed while reducing overall bandwidth consumption.
Solution Approach 2:
The patent segments the display screen into multiple regions: a region of interest (ROI) where HD video is rendered, and other regions where SD video is displayed. This segmentation allows the system to allocate bandwidth selectively, providing high quality only where the user is attending while maintaining lower overall bandwidth requirements.
2Quantity of substance
If SD video is displayed on the display device, then bandwidth consumption is reduced, but video quality deteriorates
Solution Approach 1:
The patent applies local quality by rendering HD video only in the region of interest (ROI) where the user is looking, while displaying SD video in other regions. This is achieved by converting SD video to HD video specifically for the ROI area based on eye position detection, thereby improving video quality where needed while reducing overall bandwidth consumption.
3Manufacturing precision
If HD video is converted from SD video, then video quality on ROI is improved, but computational power requirement increases
Solution Approach 1:
The patent applies local quality by rendering HD video only in the region of interest (ROI) where the user is looking, while displaying SD video in other regions. This is achieved by converting SD video to HD video specifically for the ROI area based on eye position detection, thereby improving video quality where needed while reducing overall bandwidth consumption.
4Adaptability or versatility
If eye position detection and video conversion are performed dynamically, then user satisfaction is improved, but device complexity increases
Solution Approach 1:
The patent uses feedback from eye position detection to dynamically adjust video quality. The system detects the user's eye position, identifies the region of interest (ROI), and converts SD video to HD video in that specific region. This feedback mechanism allows the system to adapt video quality to user attention, improving user satisfaction while managing device complexity through targeted processing.
Solution Approach 2:
The patent applies dynamics by making the video quality adaptive rather than static. The system dynamically converts SD video to HD video in the region of interest based on real-time eye position detection, allowing the video quality to change according to user attention. This dynamic approach improves user satisfaction while managing computational resources efficiently.
Data Source
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AI summary
Embodiments of the present disclosure disclose a method and a device for dynamically controlling quality of a video displaying on a display associated to an electronic device is provided. The method comprises detecting the current eye position of a user and identifying at least one region of interest (ROI) on a display screen of the display device based on the current eye position of the user. Then, the method comprises predicting the next position of the eye based on at least one of the current eye position of the user or the at least one ROI. Also, the method comprises converting the SD video into a high definition (HD) video displayed on the ROI on the display screen associated with the current and next position of the eye. Further, the method comprises displaying the HD video on the ROI of the display screen.