>Magister Scientiae - MSc / In order to classify South African Sign Language as a signed gesture, five fundamental parameters need to be considered. These five parameters to be considered are: hand shape, hand orientation, hand motion, hand location and facial expressions. The research in this thesis will utilise Deep Learning techniques, specifically Convolutional Neural Networks, to recognise hand shapes in various hand orientations. The research will focus on two of the five fundamental parameters, i.e., recognising six South African Sign Language hand shapes for each of five different hand orientations. These hand shape and orientation combinations will be recognised by means of a video stream captured on a mobile device. The efficacy of Convolutional Neural Network for gesture recognition will be judged with respect to its classification accuracy and classification speed in both a desktop and embedded context. The research methodology employed to carry out the research was Design Science Research. Design Science Research refers to a set of analytical techniques and perspectives for performing research in the field of Information Systems and Computer Science. Design Science Research necessitates the design of an artefact and the analysis thereof in order to better understand its behaviour in the context of Information Systems or Computer Science. / National Research Foundation (NRF)

>Magister Scientiae - MSc / Hand shape recognition is a pivotal part of any system that attempts to implement Sign Language recognition. This thesis presents a novel system which recognises hand shapes from a single camera view in 2D. By mapping the recognised hand shape from 2D to 3D,it is possible to obtain 3D co-ordinates for each of the joints within the hand using the kinematics embedded in a 3D hand avatar and smooth the transformation in 3D space between any given hand shapes. The novelty in this system is that it does not require a hand pose to be recognised at every frame, but rather that hand shapes be detected at a given step size. This architecture allows for a more efficient system with better accuracy than other related systems. Moreover, a real-time hand tracking strategy was developed that works efficiently for any skin tone and a complex background.

>Magister Scientiae - MSc / There are five fundamental parameters that characterize any sign language gesture. They are hand shape, orientation, motion and location, and facial expressions. The SASL group at the University of the Western Cape has created systems to recognize each of these parameters in an input video stream. Most of these systems make use of the Support Vector Machine technique for the classification of data due to its high accuracy. It is, however, unknown how other machine learning techniques compare to Support Vector Machines in the recognition of each of these parameters. This research lays the foundation for the process of determining optimum machine learning techniques for each parameter by comparing Support Vector Machines to Artificial Neural Networks and Random Forests in the context of South African Sign Language hand shape recognition. Li, a previous researcher at the SASL group, created a state-of-the-art hand shape recognition system that uses Support Vector Machines to classify hand shapes. This research re-implements Li’s feature extraction procedure but investigates the use of Artificial Neural Networks and Random Forests in the place of Support Vector Machines as a comparison. The machine learning techniques are optimized and trained to recognize ten SASL hand shapes and compared in terms of classification accuracy, training time, optimization time and classification time.

People began to interact with their own environment since their birth. Their main organs to sense their surroundings are their hands, and this is the most natural way of interaction in human-human interactions. The goal of this dissertation is to enable users to employ their hands in interaction with computers similar to human-human interaction. Using hands in the computer interaction increases both the naturalness of computer usage and the speed of interaction. One way of accomplishing this goal is to utilize computer vision methods to develop hand interfaces. In this study, a regular, low-cost camera is used for image acquisition, and the images from camera are processed by our novel vision system to detect user intention. The contributions are (i) a method for interacting with a screen without touching in a distributed computer system is proposed, (ii) a benchmark of four hand shape representation methods is performed using a comprehensive hand shape video database, and (iii) a vison-based hand interface is designed for an application that queries a video database system, and its usability and performances are also assessed by a group of test users to determine its suitability for the application.

La biométrie est une alternative qui se base sur l'identification des personnes à partir de leurs caractéristiques physiques (empreinte digitale, forme de la main, empreinte palmaire) et/ou comportementales (voix, signature dynamique). La biométrie tend à réaliser deux buts importants dans notre vie courante. Le premier but est de réaliser la sécurité en éliminant le doute sur l'identité d'une personne et le second but est de faciliter l'identification des individus. En effet, cette méthode d'identification est de plus en plus préférée par rapport aux méthodes traditionnelles impliquant les mots de passe et les badges. Les travaux de recherche de cette thèse s'inscrivent dans le cadre de la reconnaissance de personnes à l'aide de la biométrie de la main. L'objectif principal est de concevoir un système biométrique multimodal basé sur la fusion de la forme de la main et de l'empreinte palmaire.La première partie de cette thèse propose un nouveau système uni-modal de vérification de la forme de la main. En effet, ce système est basé d'une part, sur la détection du meilleur ensemble des points-clés localisés sur le contour de la main pour adopter la description SIFT (Scale Invariant Feature Transform). D'autre part, un raffinement de correspondance, basé région et apparence de la main est proposé, afin de raffiner autant que possible les points-clés faussement matchés.Tandis que la deuxième partie consiste à proposer un nouveau système d'identification palmaire. En effet, la méthode de représentation parcimonieuse est adoptée afin de décrire le trait biométrique de l'empreinte palmaire. Elle est basée sur l'extraction de descripteurs SIFT de chacun des points-clés détectés. Notre troisième partie concerne la proposition de différentes méthodes de fusion multi-types de la multi modalité, comprenant la fusion multi-représentation, la fusion multi-biométrique et la fusion multi-instance. En effet, la fusion multi-représentation est basée sur la combinaison de descripteurs SIFT et les caractéristiques géométriques de la main au niveau des scores, pour la vérification de la forme de la main. La fusion multi-biométrique est basée sur la combinaison des deux modalités biométriques à savoir la forme de la main et l'empreinte palmaire, au niveau des caractéristiques et de la décision. Par contre, la fusion multi-instance est basée sur la combinaison des empreintes palmaires droite et gauche, au niveau du rang.Ces différentes méthodes de fusion ont prouvé leur efficacité en obtenant de meilleurs taux de reconnaissance, qui sont compétitifs par rapport à d'autres approches multimodales de la biométrie de la main. / Biometry is a technology which is based on the personal identification using their physical features (fingerprint, hand geometry, palmprint) and/or behavioral features (voice, dynamic signature). Biometry aims to achieve two important goals in our current life. The first one is to ensure security by eliminating doubt regarding the identity of a person and the second one is to facilitate the identification of individuals. Indeed, this method of identification is increasingly preferred over traditional methods including passwords and badges. The research works of this thesis talk about the personal recognition using hand biometrics. The main objective is to design a multimodal biometric system based on the fusion of hand shape and palmprint modalities.Our first part is to propose a new unimodal biometric system for hand shape verification. In fact, this system is based firstly, on the detection of the best set of keypoints located on the contour of the hand for further SIFT (Scale Invariant Feature Transform) description. On the other hand, a matching refinement based hand region and appearance is proposed in order to refine as much as possible false matched keypoints.Our second part consists in the proposition of a new palmprint identification system. In fact, the sparse representation method is adopted in order to describe the palmprint biometric trait. It is based on the extraction on SIFT descriptors for each detected keypoint.Our third part concerns the proposition of multi-type fusion methods for multimodality, including the multi-representation fusion, the multi-biometric fusion and the multi-instance fusion. Indeed, the multi-representation fusion method is based on the combination of SIFT descriptors and geometrical features of the hand, at score level. The multi-biometric fusion method is based on the fusion of hand shape and palmprint modalities, at feature and decision levels. On the other hand, the multi-instance fusion method is based on the combination of left and right palmprints, at rank level.These different methods of fusion have proven their effectiveness by achieving encouraging recognition rates that are competitive to other popular multimodal hand biometric approaches.

Mastering the physical aspect of piano technique has long been a topic of great interest and importance to pianists. This is borne out in the numerous pedagogical approaches on the topic of piano technique. Despite the many contributions from pedagogues and scholars in developing an understanding of piano technique, many conflicting approaches often cause more confusion than clarity. After reviewing the literature on pedagogical approaches to piano technique, this study determined that problematic language might lie at the root of the confusion. Core concepts identified in the review of literature as recurring areas of misunderstanding were tension, relaxation, co-contraction, arm weight, and hand and finger shape. The purpose of this study is to seek where issues of language exist in contemporary piano pedagogical approaches and to show how these problems may contribute to the systemic confusion in piano technique. To do this, the language that is used to describe and define the core concepts identified in the review of literature is analyzed in five modern pedagogical approaches. Five authors who have developed approaches that reflect current trends in piano technique have been selected for this study: Barbara Lister-Sink; Dorothy Taubman; Thomas Mark; Fred Karpoff; and Alan Fraser. The first step of this study entails collecting data from each of the five pedagogical approaches. The data is then analyzed for consistency and accuracy. Problems in language that contribute to the inconsistencies and inaccuracies are examined and illustrated with material from the data collection. This study concludes by identifying the main sources of confusion in the use of language: inconsistent and inaccurate use of terms; wavering between scientific, common, and invented language; challenges in describing opposing qualities that come from tension and relaxation; and failing to discern between the individual subjective experience and the mechanics of movement. By recognizing where the problems in language exist, this study represents an important first step for the pedagogical community to reach a common understanding of the language used to describe the physical aspect of piano technique.

Mastering the physical aspect of piano technique has long been a topic of great interest and importance to pianists. This is borne out in the numerous pedagogical approaches on the topic of piano technique. Despite the many contributions from pedagogues and scholars in developing an understanding of piano technique, many conflicting approaches often cause more confusion than clarity. After reviewing the literature on pedagogical approaches to piano technique, this study determined that problematic language might lie at the root of the confusion. Core concepts identified in the review of literature as recurring areas of misunderstanding were tension, relaxation, co-contraction, arm weight, and hand and finger shape. The purpose of this study is to seek where issues of language exist in contemporary piano pedagogical approaches and to show how these problems may contribute to the systemic confusion in piano technique. To do this, the language that is used to describe and define the core concepts identified in the review of literature is analyzed in five modern pedagogical approaches. Five authors who have developed approaches that reflect current trends in piano technique have been selected for this study: Barbara Lister-Sink; Dorothy Taubman; Thomas Mark; Fred Karpoff; and Alan Fraser. The first step of this study entails collecting data from each of the five pedagogical approaches. The data is then analyzed for consistency and accuracy. Problems in language that contribute to the inconsistencies and inaccuracies are examined and illustrated with material from the data collection. This study concludes by identifying the main sources of confusion in the use of language: inconsistent and inaccurate use of terms; wavering between scientific, common, and invented language; challenges in describing opposing qualities that come from tension and relaxation; and failing to discern between the individual subjective experience and the mechanics of movement. By recognizing where the problems in language exist, this study represents an important first step for the pedagogical community to reach a common understanding of the language used to describe the physical aspect of piano technique.

Mastering the physical aspect of piano technique has long been a topic of great interest and importance to pianists. This is borne out in the numerous pedagogical approaches on the topic of piano technique. Despite the many contributions from pedagogues and scholars in developing an understanding of piano technique, many conflicting approaches often cause more confusion than clarity. After reviewing the literature on pedagogical approaches to piano technique, this study determined that problematic language might lie at the root of the confusion. Core concepts identified in the review of literature as recurring areas of misunderstanding were tension, relaxation, co-contraction, arm weight, and hand and finger shape. The purpose of this study is to seek where issues of language exist in contemporary piano pedagogical approaches and to show how these problems may contribute to the systemic confusion in piano technique. To do this, the language that is used to describe and define the core concepts identified in the review of literature is analyzed in five modern pedagogical approaches. Five authors who have developed approaches that reflect current trends in piano technique have been selected for this study: Barbara Lister-Sink; Dorothy Taubman; Thomas Mark; Fred Karpoff; and Alan Fraser. The first step of this study entails collecting data from each of the five pedagogical approaches. The data is then analyzed for consistency and accuracy. Problems in language that contribute to the inconsistencies and inaccuracies are examined and illustrated with material from the data collection. This study concludes by identifying the main sources of confusion in the use of language: inconsistent and inaccurate use of terms; wavering between scientific, common, and invented language; challenges in describing opposing qualities that come from tension and relaxation; and failing to discern between the individual subjective experience and the mechanics of movement. By recognizing where the problems in language exist, this study represents an important first step for the pedagogical community to reach a common understanding of the language used to describe the physical aspect of piano technique.

Magister Scientiae - MSc / Research has shown that five fundamental parameters are required to recognize any sign language gesture: hand shape, hand motion, hand location, hand orientation and facial expressions. The South African Sign Language (SASL) research group at the University of the Western Cape (UWC) has created several systems to recognize sign language gestures using single parameters. These systems are, however, limited to a vocabulary size of 20 – 23 signs, beyond which the recognition accuracy is expected to decrease. The first aim of this research is to investigate the use of two parameters – hand motion and hand shape – to recognise a larger vocabulary of SASL gestures at a high accuracy. Also, the majority of related work in the field of sign language gesture recognition using these two parameters makes use of Hidden Markov Models (HMMs) to classify gestures. Hidden Markov Support Vector Machines (HM-SVMs) are a relatively new technique that make use of Support Vector Machines (SVMs) to simulate the functions of HMMs. Research indicates that HM-SVMs may perform better than HMMs in some applications. To our knowledge, they have not been applied to the field of sign language gesture recognition. This research compares the use of these two techniques in the context of SASL gesture recognition. The results indicate that, using two parameters results in a 15% increase in accuracy over the use of a single parameter. Also, it is shown that HM-SVMs are a more accurate technique than HMMs, generally performing better or at least as good as HMMs.

Mastering the physical aspect of piano technique has long been a topic of great interest and importance to pianists. This is borne out in the numerous pedagogical approaches on the topic of piano technique. Despite the many contributions from pedagogues and scholars in developing an understanding of piano technique, many conflicting approaches often cause more confusion than clarity. After reviewing the literature on pedagogical approaches to piano technique, this study determined that problematic language might lie at the root of the confusion. Core concepts identified in the review of literature as recurring areas of misunderstanding were tension, relaxation, co-contraction, arm weight, and hand and finger shape. The purpose of this study is to seek where issues of language exist in contemporary piano pedagogical approaches and to show how these problems may contribute to the systemic confusion in piano technique. To do this, the language that is used to describe and define the core concepts identified in the review of literature is analyzed in five modern pedagogical approaches. Five authors who have developed approaches that reflect current trends in piano technique have been selected for this study: Barbara Lister-Sink; Dorothy Taubman; Thomas Mark; Fred Karpoff; and Alan Fraser. The first step of this study entails collecting data from each of the five pedagogical approaches. The data is then analyzed for consistency and accuracy. Problems in language that contribute to the inconsistencies and inaccuracies are examined and illustrated with material from the data collection. This study concludes by identifying the main sources of confusion in the use of language: inconsistent and inaccurate use of terms; wavering between scientific, common, and invented language; challenges in describing opposing qualities that come from tension and relaxation; and failing to discern between the individual subjective experience and the mechanics of movement. By recognizing where the problems in language exist, this study represents an important first step for the pedagogical community to reach a common understanding of the language used to describe the physical aspect of piano technique.