PMVS算法的CPU多线程和GPU两级粒度并行策略

Multithread and GPU Parallel Schema on Patch-based Multi-view Stereo Algorithm

PMVS(Patch-based Multi-View Stereo)三维重建算法被广泛应用于无人机航拍影像的三维场景重建中。针对PMVS三维重建算法计算量大、时间复杂度高的问题,提出了PMVS算法的CPU多线程和GPU两级粒度并行策略(Multithread and GPU Parallel Schema,MGPS),方法具体包括:基于GPU的PMVS算法特征提取和片面扩散的并行设计;多影像的GPU和CPU任务分配机制,以使得部分任务分配给CPU采用多线程并行,部分任务分配给GPU并行时,程序总运行时间最短。实验采用搭载24核CPU和NVIDIA Tesla K20GPU的高性能服务器作为测试平台,针对分辨率为4081×2993的16幅无人机影像进行三维重建。实验结果表明,相比串行的PMVS算法,基于MGPS的PMVS算法取得4倍左右的加速比,其中特征提取最高加速13倍,计算误差在10%以内,该方法实现了更高效的PMVS三维重建。基于MGPS的PMVS算法还可用于文物保护、医学图像处理、虚拟现实等领域。

PMVS（Patch-based Multi-view Stereo）has been widely used in the 3Dreconstruction,with the aerial photo of the UAV（Unmanned Aerial Vehicle）.To solve the problem of the time complexity and calculation amount of PMVS,this paper proposed the two-level parallel schema of CPU multi-thread and GPU for PMVS.The solution includes GPU-based parallel design and optimization and task allocation mechanism of the images between the GPU and CPU.The experiments have been done on the platform with a 24-core CPU and NVIDIA Tesla K20 GPU high-performance server,with 16 remote sensing images having the resolution of 4081×2993.Compared with the serial traditional PMVS,the experiment results show that our model MGPS（the two-level parallel schema of CPU multi-thread and GPU for PMVS）can be 13 times faster at feature extraction,4times faster at PMVS.Calculation error is less than 10%.MGPS shortens the execution time of PMVS algorithm.PMVS based on MGPS algorithm can also be used in the field of cultural relic protection,medical image processing,virtual reality and so on.