The rapid expansion of the metaverse and immersive computing platforms is driving unprecedented demand for efficient multi-view content delivery. Companies face intense pressure to reduce operational costs associated with data transmission and storage while simultaneously enhancing user experience. This technology provides a critical solution, enabling businesses to meet these dual demands, gain a competitive edge in next-gen media, and comply with evolving data efficiency standards across global markets.
Optimizes encoding bitrates by depth, reducing data volume while maintaining quality in critical visual areas.
Minimizes image quality degradation in critical depth segments compared to uniform compression, enabling more realistic immersive experiences.
Reduces latency in real-time applications like VR/AR and remote operation by improving encoding/decoding efficiency.
This patent, comprising 8 claims, robustly protects the core aspects of generating depth-specific layered view images and controlling their encoding bitrates. Its distinctiveness was recognized despite five prior art references, demonstrating strong differentiation and stable, superior rights.
This patent primarily covers depth-aware multi-view image encoding and decoding. White space exists in novel hardware implementations for depth sensing, advanced adaptive streaming protocols for compressed multi-view data, or AI-driven multi-view content generation.
If annual multi-view image data storage and communication costs are ~$650K (AI est.), this technology could reduce costs by approximately 20%, leading to an estimated annual saving of ~$150K (AI est.). This assumes an average bitrate reduction of over 15% through depth-specific optimized encoding, directly optimizing communication bandwidth and storage capacity, significantly lowering operational costs for adopting companies.
X: Cost Efficiency (Cost Reduction & Quality Preservation)
Y: Immersive Experience Quality (Real-time & High Definition)