Scrolling Motion Detection in Video Stream Encoding
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Solution Overview
Problem
Video conferencing experiences limitations in video and audio quality due to bandwidth constraints, particularly during screen sharing, where traditional encoding methods struggle with the unique characteristics of screen video sequences containing text, graphics, and natural images, leading to irregular bitrates and network congestion.
Innovation Solution
An adaptive encoding strategy is implemented, utilizing multiple reference picture selection, temporal sub-layer switching, and content analysis to control bitrates and optimize screen video encoding, including the use of long-term and short-term reference pictures, and synchronous P picture encoding to manage network conditions and client capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional encoding methods are used for screen video, then device complexity is low, but video quality deteriorates due to irregular bitrates and network congestion
Solution Approach 1:
The patent implements dynamic adaptive encoding by continuously monitoring network conditions and adjusting encoding parameters in real-time. The system dynamically switches between different encoding modes (e.g., H.264, H.265) and adjusts bitrates based on network availability, ensuring stable video quality transmission despite varying network conditions.
Solution Approach 2:
The system changes multiple encoding parameters simultaneously including bitrate, frame rate, resolution, and encoding mode based on network conditions. By adjusting these parameters adaptively, the system optimizes the balance between video quality and network bandwidth utilization, resolving the contradiction between quality and complexity.
2Reliability
If adaptive encoding with multiple reference pictures is used, then video quality improves, but processing time increases
Solution Approach 1:
The system performs preliminary analysis of screen content characteristics before encoding, identifying whether the content is text-dominated, graphic-dominated, or natural image-dominated. This preliminary classification allows the encoder to pre-select appropriate reference picture strategies and encoding modes, reducing real-time processing time while maintaining quality.
Solution Approach 2:
The patent segments the screen video into different content types (text regions, graphic regions, natural image regions) and applies different encoding strategies to each segment. By segmenting the processing task, the system can optimize each segment independently, reducing overall processing time compared to uniform encoding of the entire frame.
3Adaptability or versatility
If screen video is transmitted over network, then communication enables remote collaboration, but network congestion occurs due to data bursts
Solution Approach 1:
The system implements periodic buffering and throttling of video data transmission. Instead of continuous transmission, the encoder buffers video frames and releases them in controlled periodic intervals based on network conditions, preventing data bursts that cause network congestion while maintaining communication capability.
Solution Approach 2:
The patent implements feedback mechanisms where the encoder continuously monitors network conditions, packet loss rates, and transmission quality, then adjusts encoding parameters accordingly. This feedback loop allows the system to adapt to network changes in real-time, preventing congestion by reducing transmission rate when network conditions deteriorate.
4Reliability
If high bitrate encoding is used, then visual quality improves, but bandwidth consumption increases
Solution Approach 1:
The system applies different encoding qualities to different regions of the screen video based on their importance and content characteristics. Text and graphic regions receive higher quality encoding when network conditions permit, while natural image regions may use lower quality encoding, optimizing the balance between visual quality and bandwidth consumption locally across the frame.
Solution Approach 2:
The bitrate is dynamically adjusted based on real-time network conditions and content importance. When network bandwidth is available, the system increases bitrate for high-quality encoding; when bandwidth is constrained, it reduces bitrate to prevent congestion, maintaining optimal quality-to-bandwidth ratio throughout transmission.
Data Source
AI summary
Scrolling motion is detected within a video stream to output an indication of a scrolling motion vector for use in encoding a current picture of the video stream. A first line of pixels within a motion region of the current picture is identified. A second line of pixels matching the first line of pixels is identified within a last played picture of the video stream. The scrolling motion vector is determined based on a comparison of lines of pixels nearby the second line of pixels within the last played picture. The indication of the scrolling motion vector is then output for use in encoding the current picture.