Evaluation of sign language learning tools: Understanding features for improved collaboration and communication between a parent and a child

Deaf children with hearing parents typically have issues with learning sign language fluently and developing literacy. In addition, these children rarely establish a strong, interpersonal bond with their caregiver. Currently, there are insufficient resources for helping bridge the gap between deaf children and hearing caregivers. This thesis proposes to explore solutions and evaluate their effectiveness with both the hearing parents and deaf children. Multiple mediums are investigated for the purposes of uncovering the most effective combination of sign language learning methodologies. This research will help designers better understand the world of deafness and how to design instructional tools that effectively utilize information about the needs and customs of the Deaf community

Real-time Immersive human-computer interaction based on tracking and recognition of dynamic hand gestures

With fast developing and ever growing use of computer based technologies, human-computer interaction (HCI) plays an increasingly pivotal role. In virtual reality (VR), HCI technologies provide not only a better understanding of three-dimensional shapes and spaces, but also sensory immersion and physical interaction. With the hand based HCI being a key HCI modality for object manipulation and gesture based communication, challenges are presented to provide users a natural, intuitive, effortless, precise, and real-time method for HCI based on dynamic hand gestures, due to the complexity of hand postures formed by multiple joints with high degrees-of-freedom, the speed of hand movements with highly variable trajectories and rapid direction changes, and the precision required for interaction between hands and objects in the virtual world. Presented in this thesis is the design and development of a novel real-time HCI system based on a unique combination of a pair of data gloves based on fibre-optic curvature sensors to acquire finger joint angles, a hybrid tracking system based on inertia and ultrasound to capture hand position and orientation, and a stereoscopic display system to provide an immersive visual feedback. The potential and effectiveness of the proposed system is demonstrated through a number of applications, namely, hand gesture based virtual object manipulation and visualisation, hand gesture based direct sign writing, and hand gesture based finger spelling. For virtual object manipulation and visualisation, the system is shown to allow a user to select, translate, rotate, scale, release and visualise virtual objects (presented using graphics and volume data) in three-dimensional space using natural hand gestures in real-time. For direct sign writing, the system is shown to be able to display immediately the corresponding SignWriting symbols signed by a user using three different signing sequences and a range of complex hand gestures, which consist of various combinations of hand postures (with each finger open, half-bent, closed, adduction and abduction), eight hand orientations in horizontal/vertical plans, three palm facing directions, and various hand movements (which can have eight directions in horizontal/vertical plans, and can be repetitive, straight/curve, clockwise/anti-clockwise). The development includes a special visual interface to give not only a stereoscopic view of hand gestures and movements, but also a structured visual feedback for each stage of the signing sequence. An excellent basis is therefore formed to develop a full HCI based on all human gestures by integrating the proposed system with facial expression and body posture recognition methods. Furthermore, for finger spelling, the system is shown to be able to recognise five vowels signed by two hands using the British Sign Language in real-time

Supporting Collaborative Learning in Computer-Enhanced Environments

As computers have expanded into almost every aspect of our lives, the ever-present graphical user interface (GUI) has begun facing its limitations. Demanding its own share of attention, GUIs move some of the users\u27 focus away from the task, particularly when the task is 3D in nature or requires collaboration. Researchers are therefore exploring other means of human-computer interaction. Individually, some of these new techniques show promise, but it is the combination of multiple approaches into larger systems that will allow us to more fully replicate our natural behavior within a computing environment. As computers become more capable of understanding our varied natural behavior (speech, gesture, etc.), the less we need to adjust our behavior to conform to computers\u27 requirements. Such capabilities are particularly useful where children are involved, and make using computers in education all the more appealing. Herein are described two approaches and implementations of educational computer systems that work not by user manipulation of virtual objects, but rather, by user manipulation of physical objects within their environment. These systems demonstrate how new technologies can promote collaborative learning among students, thereby enhancing both the students\u27 knowledge and their ability to work together to achieve even greater learning. With these systems, the horizon of computer-facilitated collaborative learning has been expanded. Included among this expansion is identification of issues for general and special education students, and applications in a variety of domains, which have been suggested

Generating realistic, animated human gestures in order to model, analyse and recognize Irish Sign Language

The aim of this thesis is to generate a gesture recognition system which can recognize several signs of Irish Sign Language (ISL). This project is divided into three parts. The first part provides background information on ISL. An overview of the ISL structure is a prerequisite to identifying and understanding the difficulties encountered in the development of a recognition system. The second part involves the generation of a data repository: synthetic and real-time video. Initially the synthetic data is created in a 3D animation package in order to simplify the creation of motion variations of the animated signer. The animation environment in our implementation allows for the generation of different versions of the same gesture with slight variations in the parameters of the motion. Secondly a database of ISL real-time video was created. This database contains 1400 different signs, including motion variation in each gesture. The third part details step by step my novel classification system and the associated prototype recognition system. The classification system is constructed as a decision tree to identify each sign uniquely. The recognition system is based on only one component of the classification system and has been implemented as a Hidden Markov Model (HMM)

Real-time immersive human-computer interaction based on tracking and recognition of dynamic hand gestures

With fast developing and ever growing use of computer based technologies, human-computer interaction (HCI) plays an increasingly pivotal role. In virtual reality (VR), HCI technologies provide not only a better understanding of three-dimensional shapes and spaces, but also sensory immersion and physical interaction. With the hand based HCI being a key HCI modality for object manipulation and gesture based communication, challenges are presented to provide users a natural, intuitive, effortless, precise, and real-time method for HCI based on dynamic hand gestures, due to the complexity of hand postures formed by multiple joints with high degrees-of-freedom, the speed of hand movements with highly variable trajectories and rapid direction changes, and the precision required for interaction between hands and objects in the virtual world. Presented in this thesis is the design and development of a novel real-time HCI system based on a unique combination of a pair of data gloves based on fibre-optic curvature sensors to acquire finger joint angles, a hybrid tracking system based on inertia and ultrasound to capture hand position and orientation, and a stereoscopic display system to provide an immersive visual feedback. The potential and effectiveness of the proposed system is demonstrated through a number of applications, namely, hand gesture based virtual object manipulation and visualisation, hand gesture based direct sign writing, and hand gesture based finger spelling. For virtual object manipulation and visualisation, the system is shown to allow a user to select, translate, rotate, scale, release and visualise virtual objects (presented using graphics and volume data) in three-dimensional space using natural hand gestures in real-time. For direct sign writing, the system is shown to be able to display immediately the corresponding SignWriting symbols signed by a user using three different signing sequences and a range of complex hand gestures, which consist of various combinations of hand postures (with each finger open, half-bent, closed, adduction and abduction), eight hand orientations in horizontal/vertical plans, three palm facing directions, and various hand movements (which can have eight directions in horizontal/vertical plans, and can be repetitive, straight/curve, clockwise/anti-clockwise). The development includes a special visual interface to give not only a stereoscopic view of hand gestures and movements, but also a structured visual feedback for each stage of the signing sequence. An excellent basis is therefore formed to develop a full HCI based on all human gestures by integrating the proposed system with facial expression and body posture recognition methods. Furthermore, for finger spelling, the system is shown to be able to recognise five vowels signed by two hands using the British Sign Language in real-time.EThOS - Electronic Theses Online ServiceGBUnited Kingdo