Acquisition of 3D shapes of moving objects using fringe projection profilometry

Three-dimensional (3D) shape measurement for object surface reconstruction has potential applications in many areas, such as security, manufacturing and entertainment. As an effective non-contact technique for 3D shape measurements, fringe projection profilometry (FPP) has attracted significant research interests because of its high measurement speed, high measurement accuracy and ease to implement. Conventional FPP analysis approaches are applicable to the calculation of phase differences for static objects. However, 3D shape measurement for dynamic objects remains a challenging task, although they are highly demanded in many applications. The study of this thesis work aims to enhance the measurement accuracy of the FPP techniques for the 3D shape of objects subject to movement in the 3D space. The 3D movement of objects changes not only the position of the object but also the height information with respect to the measurement system, resulting in motion-induced errors with the use of existing FPP technology. The thesis presents the work conducted for solutions of this challenging problem

Laser-camera composite sensing for road detection and tracing

An important feature in most urban roads and similar environments, such as in theme parks, campus sites, industrial estates, science parks, and the like, is the existence of pavements or curbs on either side de?ning the road boundaries. These curbs, which are mostly parallel to the road, can be harnessed to extract useful features of the road for implementing autonomous navigation or driver assistance systems. However, vision-alone methods for extraction of such curbs or road edge features with accurate depth information is a formidable task, as the curb is not conspicuous in the vision image and also requires the use of stereo images. Further, bad lighting, adverse weather conditions, nonlinear lens aberrations, or lens glare due to sun and other bright light sources can severely impair the road image quality and thus the operation of vision-alone methods. In this paper an alternative and novel approach involving the fusion of 2D laser range and monochrome vision image data is proposed to improve the robustness and reliability. Experimental results are presented to demonstrate the viability and effectiveness of the proposed methodology and its robustness to different road configurations and shadows