3D face modeling is currently a popular area in Computer Graphics and Computer Vision. Many techniques have been introduced for this purpose, such as using one or more cameras, 3D scanners, and many other systems of sophisticated hardware with related software. But the main goal is to find a good balance between visual reality and the cost of the system. In this thesis, reconstruction of a 3D human face from a pair of stereo cameras is studied. Unlike many other systems, facial feature points are obtained automatically from two photographs with the help of a dot pattern projected on the object&amp / #8217 / s face. It is seen that using projection pattern also provided enough feature points to derive 3D face roughly. These points are then used to fit a generic face mesh for a more realistic model. To cover this 3D model, a single texture image is generated from the initial stereo photographs.

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (p. 245-249).

Miniature cameras play a key role in numerous imaging applications ranging from endoscopy and metrology inspection devices to smartphones and head-mount acquisition systems. However, due to the physical constraints, the imaging conditions, and the low quality of small optics, their imaging capabilities are limited in terms of the delivered resolution, the acquired depth of field, and the captured dynamic range. Computational imaging jointly addresses the imaging system and the reconstructing algorithms to bypass the traditional limits of optical systems and deliver better restorations for various applications. The scene is encoded into a set of efficient measurements which could then be computationally decoded to output a richer estimate of the scene as compared with the raw images captured by conventional imagers. In this dissertation, three task-based computational imaging techniques are developed to make low-quality miniature cameras capable of delivering realistic high-resolution reconstructions, providing full-focus imaging, and acquiring depth information for high dynamic range objects. For the superresolution task, a non-regularized direct superresolution algorithm is developed to achieve realistic restorations without being penalized by improper assumptions (e.g., optimizers, priors, and regularizers) made in the inverse problem. An adaptive frequency-based filtering scheme is introduced to upper bound the reconstruction errors while still producing more fine details as compared with previous methods under realistic imaging conditions. For the full-focus imaging task, a computational depth-based deconvolution technique is proposed to bring a scene captured by an ordinary fixed-focus camera to a full-focus based on a depth-variant point spread function prior. The ringing artifacts are suppressed on three levels: block tiling to eliminate boundary artifacts, adaptive reference maps to reduce ringing initiated by sharp edges, and block-wise deconvolution or depth-based masking to suppress artifacts initiated by neighboring depth-transition surfaces. Finally for the depth acquisition task, a multi-polarization fringe projection imaging technique is introduced to eliminate saturated points and enhance the fringe contrast by selecting the proper polarized channel measurements. The developed technique can be easily extended to include measurements captured under different exposure times to obtain more accurate shape rendering for very high dynamic range objects.

An automated prototype variable rate (VR) sprayer was developed for control of eight individual nozzles on a 6.1 m sprayer boom for spot-application (SA) of agrochemicals in wild blueberry fields. The VR control system consisted of eight ultrasonic sensors and four cameras mounted on a separate boom in front of the ATV, flow controller, VR controller, ruggedized computer, flow valve and solenoid valves. Custom software was capable of processing the images to detect weeds or plants in real-time and automatically send a signal to the VR controller for SA at the correct target. The performance of VR sprayer for SA on weeds (herbicide) and foliage (fungicide) was evaluated in commercial wild blueberry fields. Based on the results of this study, the VR sprayer was reliable, efficient and accurate enough for SA of agrochemicals. The average volume of chemical saved with SA was 70 % herbicide and 30 % fungicide.

High capacity wireless and xed-line broadband services have a relatively small footprint over South Africa's vast expanse. This results in many rural areas, as well as military communication when deployed, relying on low-bandwidth communication networks instead, making live video communication over these links impractical. Traditional and advanced data compression methods cannot produce the payload reduction required for video use over these bandwidths. Instead, a model-based vision system is used to address this problem. This is not video compression but rather image understanding and representation in the context of prior models of the observed object. Markerless human tracking and pose recovery are the specific interests of this research. Markerless human pose tracking is a relatively new and growing field of image processing. It has many potential areas of application apart from low-bandwidth video communication, including the medical field, sporting arena, security and surveillance and human-machine interaction. As multimedia technologies continue to grow and improve, pose tracking systems have the potential to be used more and more. While a few markerless tracking devices are beginning to emerge, many currently available commercial motion capture systems require the use of a special suit and markers or sensors. This makes them very impractical for easy everyday, anywhere use. Current research in computer vision and image processing incorporates a significant focus on the development of markerless approaches to human motion capture. This dissertation looks at a complete markerless human pose tracking system which can be split into four distinct but interlinking stages: the image capture, image processing, body model and optimisation stages. After video data from multiple camera views is captured, the processing stage extracts image cues such as silhouettes, 2-D edges and 3-D colour volumetric reconstruction. Following the basic principle of a model-based approach, a 24 degree-of-freedom superellipsoid body model is fitted to the observed image cue data. An objective function is used to measure the closeness of this match. A number of different optimisation approaches are examined for use in refining and finding the best fitting body pose for each image frame. These approaches are all based around Stochastic Meta Descent (SMD) optimisation with SMD by itself, SMD in a hierarchical approach, SMD with pose prediction and Smart Particle Filtering, SMD inside a particle filter framework, all explored. The performance of the system with the various optimisation approaches is tested using the HumanEvaII datasets. These datasets contain a number of different subjects performing a variety of actions while wearing ordinary clothes. They contain markerbased ground-truth data obtained using a ViconPeak motion capture system. This allows a relative error measurement of the predicted poses to be calculated. With its robustness to clutter and occlusion, the Smart Particle Filter approach is shown to give the best results. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2012.

Mode confusion describes the psychological condition of a human operator when he or she finds it difficult or impossible to determine the current state of an automated system. The ability for a user to keep track of these modes internally is especially important in systems where the number of available functions is greater than the number of controls or indicators present in the user interface. In this thesis, we present a set of heuristics, intended for use by engineers during design time. to mitigate mode confusion potential in digital cameras. To test the applicability and effectiveness of these heuristics, we simulated a formative evaluation, as would be performed by a designer, and correlated these results with that of a usability study.

This study examined the drivers' perception of the SAHER (means "watchful" in Arabic) system in Jeddah, Saudi Arabia. The purpose of this study was to analyze the perception of the SAHER system on impacting the overall traffic conditions in Jeddah, Saudi Arabia including its effectiveness and flaws. A survey was conducted and distributed to 70 drivers and residents of Jeddah. Drivers were divided into two groups based on their age. Five hypotheses were tested in this study. Hypotheses one through four were tested using the averages of related questions. Hypothesis five was tested statistically using a z-test for differences between the means. The overall conclusion of drivers' perception of SAHER on increasing road safety and reducing loss of life was generally positive. The conclusion for hypothesis 1, 2, and 3 was positive. The conclusion for hypothesis four was inconclusive. The conclusion for hypothesis five was retained to the null hypothesis with a 95% confidence level. A key recommendation from the study is that to measure the overall effectiveness of the system it will be prudent to observe how the system is perceived in other major cities of Saudi Arabia apart from Jeddah.

Thesis (M. Phil.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.

Dissertation (Ph.D.) -- University of Texas Southwestern Medical Center at Dallas, 2006. / Vita. Bibliography: p.97-109

Thesis (Ph. D.)--University of Missouri-Columbia, 1996. / Typescript. Vita. Includes bibliographical references (leaves 187-202). Also available on the Internet.