Image Compression via Eye-Tracking Fixation Segmentation
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Solution Overview
Problem
Virtual reality and augmented reality systems face challenges with large data volumes and high transmission bandwidth due to the need for high-definition image rendering, which can be inefficient and cumbersome.
Innovation Solution
An image compression method that identifies a human-eye fixation point on an original image, separates it into a fixation region and a non-fixation region, and compresses the non-fixation region using down-sampling and rearrangement techniques, while maintaining high-definition rendering of the fixation region.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-definition image rendering is used in virtual reality systems, then user sensory experience and visual quality are improved, but data volume and transmission bandwidth requirements increase significantly
Solution Approach 1:
The patent divides the image into a fixation region and a non-fixation region based on eye tracking data. The fixation region (where the user's eyes are focused) is maintained at high definition, while the non-fixation region is compressed. This segmentation allows the system to allocate computational and bandwidth resources efficiently, maintaining high image quality where needed while reducing overall data volume.
Solution Approach 2:
The patent applies different quality levels to different regions of the image. The fixation region maintains full resolution and detailed rendering, while the non-fixation region uses reduced resolution and compression. This local quality differentiation ensures that high visual quality is concentrated in the area most important to the user's perception, while reducing the total data burden.
2Reliability
If high-performance computing systems with central processors are used to simulate virtual three-dimensional worlds, then sensory experience and immersion are improved, but system complexity and computational burden increase
Solution Approach 1:
The computing system segments the image processing task into two parts: processing the fixation region at full computational detail, and processing the non-fixation region at reduced detail. This segmentation reduces the overall computational burden while maintaining the immersive sensory experience in the critical fixation area.
Solution Approach 2:
The system applies full computational processing only where necessary (fixation region) and uses partial processing for the rest (non-fixation region). This partial action approach reduces the total computational resources required while maintaining sufficient quality for user immersion, avoiding the excessive computational cost of processing the entire image at full resolution.
3Quantity of substance
If the entire image is compressed uniformly, then data volume is reduced, but image quality and user perception are degraded
Solution Approach 1:
The patent segments the image into fixation and non-fixation regions, applying compression selectively only to the non-fixation region while maintaining the fixation region at full quality. This segmented compression approach reduces overall data volume while preserving image quality in the critical area where the user is focused.
Solution Approach 2:
The system maintains high local quality in the fixation region and applies compression only to the non-fixation region. This local quality differentiation ensures that image quality is preserved where the user is most attentive while reducing data volume through compression in less critical areas.
Data Source
AI summary
The present disclosure provides an image compression method, including steps of: acquiring a human-eye fixation point on an original image, and determining a fixation region and a non-fixation region of the original image according to the human-eye fixation point; and compressing the non-fixation region, and generating a compressed image according to the fixation region and the compressed non-fixation region. The present disclosure also provides an image display method, an image compression apparatus, an image display apparatus, and a computer readable medium.