Massively parallel inverse rendering using Multi-objective Particle Swarm Optimization

We present a novel GPU-accelerated per-pixel inverse rendering optimization algorithm based on Particle Swarm Optimization (PSO). Our algorithm estimates the per-pixel scene attributes—including reflectance properties—of a 3D model, and is fast enough to do in situ visualization of the optimization in real-time. The algorithm’s high parallel efficiency is demonstrated through our GPU/GLSL shader implementation of the method. IRPSO is validated experimentally on simulated ground truth images, while a suite of tests performed on the University of Southern California’s High Performance Computing Center cluster provides strong evidence that our method can scale to larger, more difficult inverse rendering problems.