GPU-accelerated uncapacitated facility location and semi-dense SymStereo pipelines for piecewise-planar-based 3D reconstruction

Abstract

Planar 3D reconstruction presents advantages over point cloud representations. This work focuses on the acceleration of piecewise-planar-based 3D reconstruction, a StereoScan method. We identify the SymStereo (logN) and uncapacitated facility location (UFL) algorithms as the most computationally expensive tasks, consuming nearly 80 × of total runtime, when detecting planes in a single stereo pair on a sequential CPU pipeline. Consequently, these algorithms have been parallelized using single- and multi-GPU architectures to perform significantly faster than previous sequential approaches. Experimental results show that accelerated parallel implementations of SymStereo (logN) can process up to 56 frames per second, achieving a speedup of 38 × against the sequential C implementation (Intel Core i7-4790k). The parallel version of the message-passing algorithm (max-sum) for the UFL problem processes up to five matrices per second and outperforms the sequential C baseline for computing UFL by 38 ×.