Computer methods for 3D motion tracking in real-time

Boguslaw Rymut; Computer methods for 3D motion tracking in real-time; PhD Thesis; 2016
Supervisor: Bogdan Kwolek, DSc, PhD, Eng., Associate Prof
Keywords: model-based 3D motion tracking, parallel computing, computer vision


This thesis is devoted to marker-less 3D human motion tracking in calibrated and synchronized multicamera systems. Pose estimation is based on a 3D model, which is transformed into the image plane and then rendered. Owing to elaborated techniques the tracking of the full body has been achieved in real-time via dynamic optimization or dynamic Bayesian filtering. The objective function of a particle swarm optimization algorithm and the observation model of a particle filter are based on matching between the rendered 3D models in the required poses and image features representing the extracted person. In such an approach the main part of the computational overload is associated with the rendering of 3D models in hypothetical poses as well as determination of value of objective function. Effective methods for rendering of 3D models in real-time with support of OpenGL as well as parallel methods for determining the objective function on the GPU were developed. Several variants of objective function using both software and hardware rendering were proposed and evaluated on real data. Methods for effective rendering of 3D models in OpenGL, as well as data mapping between OpenGL and CUDA were developed and evaluated. Programmable streams in OpenGL were designed and configured to achieve real-time rendering of considerable number of 3D models in desired poses. Methods for parallel execution of particle swarm optimization as well as objective function calculation were developed to achieve effective utilization of hardware resources and the best possible tracking accuracies and frequencies. The elaborated solutions permit 3D tracking of full body motion in real-time. Certain solutions to enable selection of the number of particles and the number of iterations in the PSO algorithm, which determine the number of processed frames per second, and which in turn determines the change in the pose between consecutive frames were investigated and proposed. They make it possible to achieve the lowest errors in real-time 3D motion tracking.


PhD Thesis in PDF format
Citation in BibTeX format


@PhdThesis{RymutPhdThesis2016, author = {Bogusław Rymut}, title = {Komputerowe algorytmy ekstrakcji i śledzenia obiektów w czasie rzeczywistym}, year = {2016}, }