Client Device Motion Vector Extrapolation for Wireless Display Judder
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Solution Overview
Problem
Wireless connections in display systems often result in data delays and loss, leading to motion judder, where frames are repeated or delayed, causing discomfort, especially in virtual-reality systems that require low latency and high detail.
Innovation Solution
A method is implemented at the client device to generate the next frame by extrapolating motion vectors from the current or previous frames when display data is unavailable, allowing for the continuation of smooth image movement and reducing judder by estimating the movement of image elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If wireless transmission is used to deliver display data, then connection flexibility and mobility are improved, but data delays and data loss occur leading to motion judder
Solution Approach 1:
The system performs preliminary actions by generating predicted display data in advance when original frame data is lost or delayed. The client device creates replacement frame data using motion vectors and depth information before the missing data arrives, ensuring continuous display without interruptions or judder effects.
Solution Approach 2:
The patent introduces an intermediary mechanism - a depth map and motion vector-based prediction system - that acts as a mediator between the lost display data and the final reconstructed frame. This intermediary allows the system to generate plausible replacement data that maintains visual continuity without directly transmitting the missing original data.
2Duration of action of stationary object
If previous frames are repeated when data is lost, then display continuity is maintained, but motion judder occurs due to sudden image jumps
Solution Approach 1:
The system applies dynamics by making the replacement frame data adaptive rather than static. Instead of simply repeating the previous frame, the system dynamically generates new frame data by extrapolating motion vectors and adjusting depth information to predict what the lost frame should contain, creating a dynamic solution that maintains continuity without judder.
Solution Approach 2:
The patent changes key parameters by modifying depth map values and motion vector extrapolations to generate predicted display data. By adjusting these parameters based on motion analysis and depth information, the system creates replacement frames that match the expected visual state rather than simply copying previous frames, thereby eliminating sudden image jumps.
3Object-generated harmful factors
If motion vectors are extrapolated to generate next frame, then judder is reduced by maintaining smooth motion, but processing complexity increases
Solution Approach 1:
The system segments the image into multiple regions or blocks and processes motion vectors for each segment independently. This segmentation allows the complex extrapolation process to be divided into smaller, more manageable tasks that can be processed in parallel, reducing the overall processing complexity while maintaining the quality of motion prediction.
Solution Approach 2:
The patent applies partial action by performing motion vector extrapolation only for regions where data is lost or where motion is detected, rather than processing the entire frame uniformly. This selective approach reduces the total processing complexity while still effectively mitigating judder in the critical areas that need correction.
Data Source
AI summary
A method at a client device for mitigating motion judder in frames of an image due to display data for a particular frame being unavailable at a required time at the client device. The method involves receiving (S35) the display data for a current frame n, and generating (S3Y3) the current frame n from the received display data. Motion vectors for some elements of the image in the current frame n are obtained (S3Y1). If it is determined that display data for the next frame n+1 is not available, the next frame n+1 is generated (S3N4) from either the current frame n or a previous frame n−m, where m=1, 2, 3, etc, adjusted based on an extrapolation (S3N3) of the motion vectors for the elements of the image in either the current frame n or the previous frame n−m.