Digital Video Latency Reduction via Real-Time Geometric Warping
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Solution Overview
Problem
Digital video latency caused by compression introduces significant delays, making it unsuitable for highly interactive tasks like remote control of vehicles, where real-time precision is required, as the latency can lead to pilot-induced oscillations and loss of control.
Innovation Solution
The method involves real-time warping of digital video frames by adjusting the image model based on the camera's field of view at the time of reception, overlaying it onto the original image model, and re-projecting it to approximate a real-time view, using sensors like inertial navigation systems to correct for latency-induced geometry differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If digital video compression is used to reduce bandwidth, then transmission efficiency is improved, but video latency increases to 200-400 milliseconds
Solution Approach 1:
The system performs preliminary actions by capturing camera pose data and predicting future pose positions before the actual video frame is received and processed. This allows the warping operation to anticipate where the view should be, effectively compensating for the compression latency of 200-400 milliseconds by pre-calculating the geometric transformation needed.
Solution Approach 2:
The patent introduces an intermediary prediction model that acts as a mediator between the compressed video stream and the display system. This model predicts future camera positions and uses these predictions to warp the received frames, bridging the time gap created by compression and delivering real-time latency reduction without sacrificing bandwidth efficiency.
2Measurement precision
If video latency is reduced through compression optimization, then real-time control precision is improved, but video quality may deteriorate
Solution Approach 1:
The patent replaces the traditional approach of reducing latency through compression optimization with a geometric warping mechanism. Instead of modifying the compression algorithm to reduce latency (which would risk video quality), the system substitutes a predictive warping process that operates on already-compressed frames, achieving real-time precision for control applications without degrading video quality.
Solution Approach 2:
The system changes the parameter being optimized from compression rate to geometric transformation parameters. By adjusting the warping parameters based on predicted camera pose changes, the system achieves real-time control precision while maintaining the original video compression quality, effectively decoupling latency reduction from quality degradation.
3Loss of time
If predictive warping is applied to reduce latency, then real-time view approximation is improved, but computational complexity increases
Solution Approach 1:
The patent segments the latency reduction problem into two independent components: pose prediction and frame warping. The pose prediction operates on sensor data independently, while the warping operates on the video frame independently. This segmentation allows each component to be optimized separately, reducing overall computational complexity compared to a unified approach that would process both simultaneously.
Solution Approach 2:
The system implements dynamics by using real-time camera pose predictions that continuously update the warping transformation. Rather than using static pre-computed warping parameters, the system dynamically adjusts the warping based on predicted pose changes, achieving accurate real-time view approximation while managing computational load through efficient dynamic updates.
Data Source
AI summary
In one aspect, video latency reduction by real-time warping is described. In one aspect, an original geometric image model of a digital video frame is adjusted according to a video frame latency, to form an adjusted geometric image model. A geometric image model may represent a field of view from a remote camera used to capture the digital video frame. The adjusted geometric image model may be overlaid onto the original geometric image model to capture a warped image. In one aspect the warped image is re-projected according to the adjusted geometric image model to form a re-projected image. The re-projected image may then be displayed to approximate a real-time field of view from a camera used to capture the digital video frame. In one aspect, an attitude and runway alignment of an unmanned aerial vehicle may be controlled using a displayed, re-projected image. Other aspects are described and claimed.