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 ×.

平面3D重建具有优于点云表示的优势。这项工作集中在加速基于分段平面的3D重建（StereoScan方法）上。我们将SymStereo（log N）和无能力设施定位（UFL）算法确定为计算上最昂贵的任务，当在顺序CPU管道上的单个立体声对中检测平面时，将消耗总运行时间的近80倍。因此，这些算法已经使用单GPU和多GPU架构进行了并行化，以比以前的顺序方法更快地执行。实验结果表明，SymStereo的并行加速实现（日志N）可以每秒处理多达56帧，相对于顺序C实现（Intel Core i7-4790k）可以达到38倍的加速。用于UFL问题的消息传递算法（最大和）的并行版本每秒处理多达5个矩阵，并且比连续C基线计算UFL的性能高38×。