Video Jitter Compensation for UAV FPV Systems
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Solution Overview
Problem
Current FPV display systems for unmanned aerial vehicles (UAVs) often suffer from jitter caused by camera movements or vibrations, leading to a non-smooth user experience, which can impair the effectiveness of aerial operations.
Innovation Solution
A system and method that processes video data from onboard imaging devices to generate stereoscopic video with reduced jitter, using multi-ocular joint encoding and virtual motion path smoothing, ensuring smooth rendering and improved user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video data is transmitted from movable object with aid of bandwidth transmission and video encoding/decoding process, then video data can be transmitted to terminal, but video jitter occurs due to camera movements or vibrations
Solution Approach 1:
The system performs preliminary actions by predicting future positions of the movable object and pre-calculating compensation transformations before video transmission occurs. This allows jitter compensation to be applied proactively rather than reactively, improving video stability during transmission
Solution Approach 2:
The system uses feedback from position sensors and motion data to continuously adjust video frame compensation in real-time. By monitoring actual movements and comparing them with predicted trajectories, the system dynamically corrects jitter artifacts throughout the video transmission process
2Ease of operation
If video smoothing and stereoscopic display processing are applied, then user experience is improved, but processing time and computational load increase
Solution Approach 1:
The video processing pipeline is segmented into distinct modular stages: jitter detection, position prediction, frame transformation, and stereoscopic rendering. This segmentation allows each stage to be optimized independently and processed in parallel where possible, reducing overall processing time while maintaining quality
Solution Approach 2:
The system dynamically adjusts processing parameters such as prediction horizon, transformation complexity, and rendering resolution based on available computational resources and network conditions. This allows the system to maintain high user experience quality while adapting processing time to available bandwidth and device capabilities
Data Source
AI summary
A method for processing video data of an environment includes, with aid of one or more processors individually or collectively, obtaining in or near real-time a reference position of an imaging device located on a movable object based on one or more previously traversed positions of the imaging device, and modifying an image frame in the video data to obtain a modified image frame based on the reference position of the imaging device and an actual position of the imaging device at which the image frame is taken. The one or more previously traversed positions are obtained using at least one sensor on the movable object. The video data is acquired by the imaging device.