Accelerated point set registration method

Ryan M Raettig, James D Anderson, Scott L Nykl and Laurence D Merkle

The Journal of Defense Modeling and Simulation, 2024, vol. 21, issue 4, 421-440

Abstract: In computer vision and robotics, point set registration is a fundamental issue used to estimate the relative position and orientation (pose) of an object in an environment. In a rapidly changing scene, this method must be executed frequently and in a timely manner, or the pose estimation becomes outdated. The point registration method is a computational bottleneck of a vision-processing pipeline. For this reason, this paper focuses on speeding up a widely used point registration method, the iterative closest point (ICP) algorithm. In addition, the ICP algorithm is transformed into a massively parallel algorithm and mapped onto a vector processor to realize a speedup of approximately an order of magnitude. Finally, we provide algorithmic and run-time analysis.

Keywords: Point set registration; ICP; parallel computing; GPU; CUDA; optimization (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:joudef:v:21:y:2024:i:4:p:421-440

DOI: 10.1177/15485129221150454

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