VR Flicker Detector Synchronizes Frame Rate with Light Frequency
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Solution Overview
Problem
Virtual reality systems experience perceptible flicker when capturing real-world views, leading to inaccurate representation and decreased tracking quality due to mismatched frame rates with light source frequencies, resulting in a negative user experience.
Innovation Solution
A virtual reality system detects flicker by calculating light intensity metrics and adjusting the frame rate to synchronize with the frequency of light sources, using a method that includes dividing frames into sets, detecting peaks, and applying a logarithm-odds equation to determine the likelihood of flicker, thereby providing an interactive element to change the frame rate and eliminate flicker.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the frame rate is fixed and does not match the frequency of light sources, then the system is simple to operate, but perceptible flicker occurs leading to inaccurate representation and decreased tracking quality
Solution Approach 1:
The system continuously monitors the captured frames for flicker by analyzing light intensity variations and uses this feedback to automatically adjust the frame rate. The flicker detection algorithm processes frame data and provides real-time information about lighting conditions, enabling the system to adapt the frame rate dynamically to match the frequency of light sources, thereby eliminating perceptible flicker and improving tracking quality without requiring manual user intervention
Solution Approach 2:
The frame rate is transformed from a fixed parameter to a dynamic one that automatically adapts to the lighting environment. The system implements automatic frame rate adjustment based on detected flicker characteristics, allowing the frame rate to vary in response to different light source frequencies. This dynamic adjustment ensures optimal synchronization between the capture rate and light source frequency, eliminating flicker while maintaining ease of operation through automation
2Object-affected harmful factors
If the frame rate is changed to synchronize with light source frequency, then perceptible flicker is eliminated, but the system complexity increases due to flicker detection and adjustment mechanisms
Solution Approach 1:
The system performs self-diagnosis and self-adjustment by incorporating flicker detection capabilities directly into the capture pipeline. The same processing units that handle normal frame capture also analyze for flicker conditions and automatically trigger frame rate adjustments when necessary. This self-service approach eliminates the need for external flicker detection devices or manual configuration, reducing overall system complexity while effectively eliminating perceptible flicker
Solution Approach 2:
The flicker detection and adjustment mechanism is integrated into the existing frame capture and processing system, allowing the same hardware and software components to serve multiple functions: normal image capture, flicker detection, frame rate analysis, and automatic frame rate adjustment. This multi-functionality approach avoids adding separate dedicated flicker control systems, thereby reducing device complexity while effectively addressing the harmful flicker effect
Data Source
AI summary
In one embodiment, a computing system receives one or more signals indicative of light intensities captured by one or more cameras. These signals are captured in a plurality of frames at a first frame rate. The computing system calculates light intensity metrics for each frame of the plurality of frames based on the one or more signals captured in the respective frames. The computing system detects one or more peaks based on the light intensity metrics associated with one or more frames of the plurality of frames. The one or more frames were captured in a predetermined time period. The computing system determines a likelihood of perceptible flicker based on the detected one or more peaks. The computing system generates a notification indicating the likelihood of perceptible flicker in response to a determination that the likelihood of perceptible flicker exceeds a predetermined threshold.