Adaptive Volume-Based XR Reconstruction for Compute Load Balancing

The patent implements dynamic parameter adjustment in the 3D scene reconstruction pipeline, where grid volume size, voxel size, and truncation distance are continuously adapted based on real-time computational load conditions. This allows the system to switch between high-accuracy modes (when resources are abundant) and high-speed modes (when resources are constrained), resolving the contradiction between reconstruction accuracy and processing speed through temporal dynamics rather than static parameter selection.

The patent explicitly changes physical parameters of the reconstruction algorithm (grid volume size, voxel size, truncation distance) based on computational conditions. By adjusting these parameters dynamically, the system can optimize the balance between accuracy and speed - using finer grids and smaller voxels for high accuracy when needed, and coarser grids with larger voxels for faster processing when computational resources are limited.

The patent implements an additive-only Truncated Signed Distance Function (TSDF) approach that processes only the necessary portions of the 3D scene rather than attempting to reconstruct every detail at maximum quality. This partial action principle allows the system to achieve sufficient reconstruction quality for AR applications while consuming fewer computational resources, thereby maintaining device performance for other concurrent processes.

The system dynamically monitors computational load and adjusts reconstruction parameters accordingly, allowing other device processes to receive necessary resources when the AR pipeline is not the primary computational priority. This dynamic resource allocation ensures that reconstruction quality is high when needed while preventing sustained degradation of overall device performance.