Towards markerless analysis of human motion

The topic for this thesis is the analysis of human movement, or more specifically, markerless analysis of human movement from video material. By markerless analysis is meant that the full image material is used as input in contrast with traditional marker systems that only use the positions of marker centers. The basic idea is to use more of the information in the images to improve the analysis. Starting of with the aim of markerless analysis an application is designed that use, to the subject added texture to estimate the position of the knee joint center in real images. The approach show the plausibility of using subject texture for estimation purposes. Another issue that is addressed is how one can generate synthetic image data. Using basic tools of graphics programming a virtual environment used to synthesize data is created. This environment is also used to evaluate some different camera solutions. One method to make three dimensional reconstruction from multiple images of an object is tested using the synthetic data. The method is based on a "brute force" approach and does not show good performance in terms of computing speed. With appropriate representations of the three dimensional objects, mathematical methods might speed up the analysis