Pose estimation and tracking is essential for applications involving human controls. Specifically, as the primary operating tool for human activities, hand pose estimation plays a significant role in applications such as hand tracking, gesture recognition, human-computer interaction and VR/AR. As the field develops, there has been a trend to utilize deep learning to estimate the 2D/3D hand poses using color-based information without depth data. Within the depth-based as well as color-based approaches, the research community has primarily focused on single-hand scenarios in a localized/normalized coordinate system. Due to the fact that both hands are utilized in most applications, we propose to push the frontier by addressing two-hand pose estimation in the global coordinate system using only color information. Our first chapter introduces the first system capable of estimating global 3D joint locations for both hands via only monocular RGB input images. To enable training and evaluation of the learning-based models, we propose to introduce a large-scale synthetic 3D hand pose dataset Ego3DHands. As knowledge in synthetic data cannot be directly applied to the real-world domain, a natural two-hand pose dataset is necessary for real-world applications. To this end, we present a large-scale RGB-based egocentric hand dataset Ego2Hands in two chapters. In chapter 2, we address the task of two-hand segmentation/detection using images in the wild. In chapter 3, we focus on the task of two-hand 2D/3D pose estimation using real-world data. In addition to research in hand pose estimation, chapter 4 includes our work on interactive refinement that generalizes the backpropagating refinement technique for dense prediction models.

Vehicle accidents by means of Public transport annually leads to a large number of passenger deaths and life long disablement. AsDu Toit, Martina Petronella a result, there is a need for preventative measures by identifying the psychomotor abilities of bus drivers during the recruitment and selection process of employment. The study was conducted among 398 bus drivers employed by a large bus company. The Vienna Test Battery was administered. It was found that distance estimation, ability to recognize forms and figures, concentration ability, eye-hand feet coordination and two-hand coordination predicted the effectiveness of bus drivers successfully. It is suggested that further research should focus on client services, attitude of bus drivers and learning potential, as factors that influence the effectiveness of bus drivers. / Industrial psychology / M.A. (Industrial Psychology)

Vehicle accidents by means of Public transport annually leads to a large number of passenger deaths and life long disablement. AsDu Toit, Martina Petronella a result, there is a need for preventative measures by identifying the psychomotor abilities of bus drivers during the recruitment and selection process of employment. The study was conducted among 398 bus drivers employed by a large bus company. The Vienna Test Battery was administered. It was found that distance estimation, ability to recognize forms and figures, concentration ability, eye-hand feet coordination and two-hand coordination predicted the effectiveness of bus drivers successfully. It is suggested that further research should focus on client services, attitude of bus drivers and learning potential, as factors that influence the effectiveness of bus drivers. / Industrial psychology / M.A. (Industrial Psychology)