A comparative study of GPU-accelerated multi-view sequential reconstruction triangulation methods for large-scale scenes

Abstract

The angular error-based triangulation method and the parallax path method are both high-performance methods for large-scale multi-view sequential reconstruction that can be parallelized on the GPU. We map parallax paths to the GPU and test its performance and accuracy as a triangulation method for the first time. To this end, we compare it with the angular method on the GPU for both performance and accuracy. Furthermore, we improve the recovery of path scales and perform more extensive analysis and testing compared with the original parallax paths method. Although parallax paths requires sequential and piecewise-planar camera positions, in such scenarios, we can achieve a speedup of up to 14x over angular triangulation, while maintaining comparable accuracy.