G-SHOT: GPU accelerated 3D local descriptor for surface matching
Department of Computer Science, Center for Scalable Architectures and Systems
Signature of histogram of orientations (SHOT) as a novel 3D object local descriptor can achieves a good balance between descriptiveness and robustness in surface matching. However, its computation workload is much higher than the other 3D local descriptors. This paper investigates the development of suitable massively parallel algorithms on the graphics processing unit (GPU) for computation of high density and large scale 3D object local descriptors through two alternative parallel algorithms; one exact, and one approximate. Both algorithms exhibit outstanding speedup performance. The exact parallel descriptor comes at no cost to the descriptiveness, with a speedup factor of up to 40.70, with respect to the serial SHOT on the central processing unit (CPU). The approximate version achieves a corresponding speedup factor of up to 54 with minor degradation in descriptiveness. The proposed algorithms are integrated into point cloud library (PCL), a open source project for image and point cloud.
Journal of Visual Communication and Image Representation
G-SHOT: GPU accelerated 3D local descriptor for surface matching.
Journal of Visual Communication and Image Representation,
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/1146