3D Display Depth Rescaling to Reduce Visual Fatigue

The patent applies dynamics by making the depth level adjustment adaptive and dynamic rather than static. The system continuously estimates visual fatigue based on motion vectors and depth profiles, then dynamically adjusts the depth level of the 3D image in real-time. This allows the system to respond to changing visual conditions and maintain optimal viewing comfort while minimizing image distortion through continuous adaptation.

The patent changes the depth level parameter of the 3D image based on estimated visual fatigue. By adjusting this critical parameter dynamically, the system modifies the convergence-accommodation relationship to reduce visual fatigue. The depth level is rescaled according to the calculated fatigue degree, transforming the image parameters to achieve a balance between comfort and distortion.

The patent applies local quality by adjusting the depth level differently for different regions or aspects of the 3D image based on local motion vector characteristics and depth profiles. Rather than uniformly down-scaling the entire depth level, the system identifies specific regions with high motion activity or particular depth characteristics and applies selective adjustment, thereby reducing visual fatigue in problematic areas while preserving image quality in other regions.

The patent applies partial action by selectively adjusting the depth level only where necessary based on motion vector analysis and depth profile evaluation. Instead of collectively down-scaling the entire depth level, the system applies adjustment only to the extent needed to reduce visual fatigue, leaving other portions of the image unchanged, thus avoiding excessive degradation of 3D image quality.

The patent applies feedback by using motion vectors and depth profiles as input to estimate visual fatigue, then using this estimation to feedback-adjust the depth level of the 3D image. This closed-loop system continuously monitors image characteristics, estimates fatigue levels, and adjusts the rendering parameters accordingly, improving estimation accuracy through iterative refinement rather than relying on simple one-time assumptions.

The patent replaces simple mechanical or rule-based assumptions with a more sophisticated computational model that uses motion vectors and depth profiles to estimate visual fatigue. By substituting complex calculations and data-driven models for simple assumptions, the system achieves higher estimation accuracy while managing processing complexity through efficient algorithms and selective computation based on image content.