Perception-Aware Video Level Control for Smooth Playback
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Solution Overview
Problem
Existing video playback systems face challenges in maintaining smooth playback and reducing internet lag, particularly when network signals are poor, especially for high-definition videos, which consume more network traffic and are prone to lag, while low-definition videos compromise video quality.
Innovation Solution
A video control method and apparatus that determines target forte attribute tag information to describe perception sensitivity degrees of auditory and visual parts in a video, adjusts the video level accordingly, and performs downloading and playing control to optimize video quality and reduce lag.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-definition video is played, then video quality is improved, but network traffic consumption increases and internet lag risk increases
Solution Approach 1:
The system dynamically adjusts video definition levels based on real-time network conditions and video content characteristics. The video player automatically switches between different definition levels (e.g., 1080P, 720P, 480P) to optimize the balance between video quality and network traffic consumption, rather than using a fixed definition level.
Solution Approach 2:
The system changes the video definition parameter based on network conditions and content importance. By analyzing network speed, buffer status, and video content tags (such as whether the video contains important visual information), the system adjusts the video definition parameter to achieve optimal playback quality under different conditions.
2Manufacturing precision
If high-definition video is played, then video quality is improved, but internet lag risk increases
Solution Approach 1:
The system dynamically adjusts video definition levels based on real-time network conditions and video content characteristics. The video player automatically switches between different definition levels (e.g., 1080P, 720P, 480P) to optimize the balance between video quality and network traffic consumption, rather than using a fixed definition level.
Solution Approach 2:
The system implements feedback mechanisms by monitoring network conditions, buffer status, and playback smoothness in real-time. Based on this feedback, the system adjusts the video definition level to prevent lag while maintaining quality. The feedback loop ensures that video quality is optimized without causing internet lag.
3Loss of energy
If low-definition video is played, then network traffic is saved and internet lag risk is reduced, but video quality deteriorates
Solution Approach 1:
The system applies different quality levels to different parts of the video based on content importance. By analyzing video content tags and visual information distribution, the system identifies key content areas that require higher quality and maintains high definition for those parts while using lower definition for less important parts, thus saving network traffic while preserving overall video quality.
Solution Approach 2:
The system dynamically adjusts video definition levels based on real-time network conditions and video content characteristics. The video player automatically switches between different definition levels (e.g., 1080P, 720P, 480P) to optimize the balance between video quality and network traffic consumption, rather than using a fixed definition level.
4Reliability
If low-definition video is played, then internet lag risk is reduced, but key content display effectiveness deteriorates
Solution Approach 1:
The system applies different quality levels to different parts of the video based on content importance. By analyzing video content tags and visual information distribution, the system identifies key content areas that require higher quality and maintains high definition for those parts while using lower definition for less important parts, thus saving network traffic while preserving overall video quality.
Solution Approach 2:
The system implements feedback mechanisms by monitoring network conditions, buffer status, and playback smoothness in real-time. Based on this feedback, the system adjusts the video definition level to prevent lag while maintaining quality. The feedback loop ensures that video quality is optimized without causing internet lag.
Data Source
AI summary
A video control method and apparatus, an electronic device, and a storage medium are provided. The video control method includes: determining target forte attribute tag information that matches a target video, wherein the target forte attribute tag information is used for describing perception sensitivity degrees to definitions of an auditory part and a visual part in the target video; determining, according to the target forte attribute tag information, a target video level to be used in the target video; and performing downloading and/or playing control on the target video according to the target video level.