Head-Mounted Display Predictive Rendering for Latency Compensation
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Solution Overview
Problem
Head-mounted display systems, such as VR and AR systems, suffer from latency issues due to user head movement between image rendering and display, leading to inefficiencies in resource usage and potential visual artifacts.
Innovation Solution
Implement time warping and predictive rendering techniques using motion sensors to estimate the field of view and adjust the render target buffer, ensuring adequate image data is available for display despite head movement and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image rendering is performed without predictive techniques, then rendering process is simple, but latency occurs due to head movement between rendering and display
Solution Approach 1:
The system performs preliminary actions by detecting head position and predicting future head position before completing the rendering process. Motion sensors detect current head position, the system predicts where the head will be when the image is displayed, and pre-adjusts the render target buffer accordingly. This preliminary prediction and buffer adjustment eliminates latency artifacts by ensuring the rendered image matches the actual displayed image.
Solution Approach 2:
The system dynamically adjusts the render target buffer based on real-time head motion detection and prediction. Instead of using a static rendering approach, the system continuously updates the predicted head position and modifies the render target buffer to compensate for anticipated head movement. This dynamic adaptation ensures image accuracy despite temporal delays in the rendering pipeline.
2Reliability
If render target buffer is enlarged to account for head movement, then image data availability is improved, but memory resource usage increases
Solution Approach 1:
Instead of pre-allocating excessive memory for all possible head movements, the system performs preliminary detection of actual head position and predicts specific future position. The render target buffer is then adjusted only for the predicted movement, allocating memory efficiently for the actual anticipated scenario rather than preparing for all possible movements.
Solution Approach 2:
The system dynamically changes parameters of the render target buffer based on detected and predicted head position. Rather than maintaining a fixed large buffer, the system adjusts buffer size and content to match the specific predicted head movement, optimizing memory usage for the actual viewing scenario.
3Reliability
If predictive rendering with motion sensors is implemented, then image accuracy is improved, but device complexity increases
Solution Approach 1:
The system introduces motion sensors as intermediaries between the rendering pipeline and display output. These sensors detect head position and provide input to the prediction algorithm, which then adjusts the render target buffer. This intermediary approach adds minimal complexity by inserting sensing and prediction components that bridge the gap between static rendering and dynamic display requirements.
Solution Approach 2:
The system replaces complex mechanical or optical adjustment mechanisms with computational prediction and software-based render target buffer adjustment. Instead of physically adapting the display or rendering hardware, the system uses motion detection and algorithmic prediction to dynamically modify the render target in software, reducing mechanical complexity.
Data Source
AI summary
In one example, a head mounted display system includes at least one memory; and at least one processor to execute instructions to: detect a first position and a first view direction of a head of a user based on sensor data generated by at least one of an accelerometer, at least one camera, or a gyroscope at a first point in time; determine a latency associated with a time to cause an image to be presented on the display; determine a predicted position and a predicted view direction of the head of the user at a second point in time based on the latency; render, prior to the second point in time, the image for presentation on the display based on the predicted position and the predicted view direction of the head of the user; and cause the display to present the rendered image.