How do VR systems create 3D images?

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VR systems' 3D image generation is actually based on the principle of stereo imaging. In other words, it's a system that tricks the brain's depth perception by presenting different images to each eye. At its core, it relies on a trick called **parallax**, which stems from standard left-right camera angles specific to each eye. On the hardware side, high-resolution displays (usually 1832x1920 pixels or higher) and a refresh rate of at least 90 FPS per frame are mandatory. The lenses in the headsets are also specially designed to correct asymmetric distortion and ensure proper focusing. The issue here is that the hardware isn't fast enough, leading to a delay called **motion-to-photon latency**—if this isn't below 20ms, users experience nausea. When it comes to algorithms, the most prominent approach is **foveated rendering**. This technique renders high-resolution details where the user is looking while reducing graphical quality in peripheral areas to boost performance. Eye-tracking sensors are used for this purpose. Additionally, techniques like **asynchronous spacewarp** or **reprojection** fill in frames by predicting them, thereby reducing GPU load. The debate here revolves around whether these methods work correctly in real time. Criticisms suggest that reprojection can cause visual quality degradation, especially in moving scenes, with claims that 10-15% of users notice these distortions. So, how much has Apple Vision Pro's retina scanning system advanced in this regard? Or how effective are Meta Quest's reprojection algorithms? This is actually one of the key issues preventing VR from reaching the masses.