Research Information System
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, İzmir, Turkey, 2 - 05 May 2018, pp.1-4, (Full Text)
3-dimensional (3D) measurement and modeling, latterly has become an important issue to facilitate the analysis of a real object or an environment. However, obtained data at a time by existing methods such as laser scanning, structured light and stereo vision, cannot represent the entire object or the environment due to the reflections and limited field of view of the sensors. In order to generate a full 3D model, it is necessary to make measurements from different positions and locate all of them in a common coordinate system. This procedure called as point cloud registration. In this study, to registration of point clouds without any prior information, four basic affine transformation parameters are calculated by global optimization techniques such as Differential Evolution (DE) and Particle Swarm Optimization (PSO). Algorithm performances are compared with a fast, deterministic algorithm called Iterative Closest Point (ICP) that highly used in 3D registration literature. The studies show that, global optimization algorithms are quite successful in.