3D-Curve-Skeletons are often used, because the object surface repesentation is less complex and also needs less computing power in further processing, compared to the representation created by the Medial Axis Transformation introduced 1967 by Harry Blum.
This theses aims at developing a 3D curve skelton approximation algorithm that keeps these advantages and is also able to handle different scenarios of the object surface input data.
Particle swarm optimization is an optimization technique based on simulation of the social behavior of swarms.
The goal of this thesis is to solve 6DOF local pose estimation using a modified particle swarm technique introduced by Khan et al. in 2010. Local pose estimation is achieved by using continuous depth and color data from a RGB-D sensor. Datasets are aquired from different camera poses and registered into a common model. Accuracy and computation time of the implementation is compared to state of the art algorithms and evaluated in different configurations.
