Automated 3D point cloud generation of an object surface from images using a Dense Surface Modelling algorithm is a reliable technique. Recently, this technique has been applied in numerous mapping applications such as the human face, historical building facades, digital archaeological artefact recording and forensic investigation. In this paper, the technique is applied to the mapping of the dorsal and plantar aspect of a human foot during weight-bearing, which is considered a difficult surface for 3D mapping. The purpose of the research is to develop an approach that provides low-cost, high-quality 3D surface models which can be used to study the dynamics of the foot during slow-gait. The objective of this paper is to present the techniques used and the results of this investigation.
The research results show that the total gaps in the generated 3D plantar surface, was less than 0.1 percent. However, these gaps did not reduce the anthropometric mark's positional measurement accuracy as these marks could be clearly identified in the 3D model. The 3D representation of the dorsal surface of the foot during walking exhibits significantly fewer holes than the plantar surface at about 0.02 percent. All the defined anthropometric landmarks appear clearly on the dorsum of the foot's 3D surface, thus making digital measurements on the surface an easy task. Light rays coming from the plantar surface must pass through a 12 mm tempered glass and, depending on the camera's position, some of the light rays suffered refraction and reflection, making the gaps in the plantar surface reconstruction unavoidable. However, the overall accuracy of the developed photogrammetric measurement technique is approximately 0.3mm for all the generated surfaces
