The collection of kinematic data is routinely required for the biomechanical analysis
of human movements. Available methods for obtaining kinematic data can be categorised
into (a) direct methods, which are often limited by bulky instrumentation, and (b) imagebased
methods. Current image-based methods generally necessitate the use of artificial
body markers to aid the identification of body parts.
A model-based method for the automatic tracking of human movement without the
aid of body markers was developed. The approach constructed a three-dimensional (3D)
computer graphics human body model that was customised to individual subjects via
incorporation of subject-specific anthropometric data and appropriate colouring of model
segments. Video image sequences of human movement were collected from multiple
synchronised camera views. The environment from each camera view was simulated so
that computer-generated model images containing the human body model could be
matched to the associated video images. The human body model configuration was
optimised through iterative adaptation of the model configuration in order to minimise the
RGB colour difference between the model images and video images. A number of
synthetic and video movement sequences were analysed using the tracking method.
Synthetic image sequences of rigid and articulated motion were tracked with good
accuracy. The tracking estimates obtained from video data of aerial movements were
compared to estimates obtained via established procedures to provide an indication of the
accuracy of the proposed approach. Movements that were successfully tracked returned
estimates with errors comparable to manual digitising estimates. More complex twisting
movements were tracked but with larger errors on all variables. The robustness of the
tracking system was investigated through examination of tracking results following
systematic perturbations made to selected tracking parameters. On both synthetic and real
data the tracking estimates were found to be relatiyely robust to perturbations in camera
and lighting parameters and reduced colour contrast.
It was concluded that the tracking system presents a viable method for marker-free
human movement tracking without representing a final solution to the problem.
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University