Condensing a priori data for recognition based augmented reality

My research proposes novel methods to reduce the cardinality of a priori data used in recognition based augmented reality, whilst retaining distinctive and persistent features in the sets. This research will help reduce latency and increase accuracy in recognition based pose estimation systems, thus improving the user experience for augmented reality applications.

Building the second generation of parallel/distributed virtual reality systems

We present the RhoVeR (Rhodes Virtual Reality) system and classify it as a second generation parallel/distributed virtual reality (DVR) system. We discuss the components of the system and thereby demonstrate its support for virtual reality application development, its configurable, parallel and distributed nature, and its synthesis of first generation DVR techniques.

Optometry training simulation with augmented reality and haptics

Optometry is an essential health care profession that has existed for many centuries and is still evolving. However, the training approaches for optometrists are not yet on par with the latest technological evolution. The traditional supervisor-student training mode could not provide good immersion and repeatability, while most existing vision-based computer-assisted simulations provide even worse immersion on screens. In this paper, we propose an effective system for optometry training simulation with two major components: augmented reality and haptics. These components are integrated with the actual slit lamp and are able to greatly enhance the immersion for typical optometry training tasks such as foreign body removal. Medical doctors are also involved in suggesting configurations and validating visual and haptic rendering results. Preliminary user studies show very positive feedbacks from optometry students.

Immigration Museum application: augmented reality application with animated museum guide

Starting with the Immigration Museum, this app will support Multilingual Orientation Tours to each venue of Museum Victoria.

Computer-simulated environment for training : challenge of efficacy evaluation

Computer-assisted instruction has been around for decades. There has been much speculation about the benefits of computer-mediated learning. Numerous applications have been developed in different domains incorporated with emerging technologies. In recently years, advanced technologies, such as Augmented Reality (AR) and Virtual Reality (VR), have received much attention in their potential of creating interactive learning experience for the users. However, related literature and empirical studies indicated that learning effects in computer-simulated environments or Virtual Environments (VEs) are not systematically tested. Furthermore, the performance and learning in computer-simulated learning environment need to be evaluated through more rigorous methods. This paper suggests that 1) the efficacy of VEs is subject to a close examination, not only in terms of how VE-based training systems are easy of use, but also in terms of how effective learning is; 2) evaluation of learning in computer simulated learning environments is required to be reconsidered in terms of theoretical basis and evaluation methodologies that are relevant to the measurement of training effectiveness in computer-simulated virtual learning environment. This paper explains on how learning can be assessed in VEs through the lens of training evaluation.

Haptics and virtual reality in modern manufacturing

Product assembly is one of the most studied processes in modern manufacturing. In recent years a number of computer-based virtual reality systems have been proposed, developed and adopted by the manufacturing industries. Such systems have major advantages over conventional training practices for product assembly. Significant cost savings can be realized due to shorter training-scenario development times and reuse of existing engineering math models. In addition, the time span from the product design to full production can be shortened due to non-reliance on actual components and subsystems for training. Such training systems are effective if the knowledge required to be transferred is just process sequence such as assembly sequence. However, knowledge transfer for procedural and cognitive learning as well as skills development is very limited, due to the lack of user interactivity and immersion.

This talk will focus on a research technology platform where haptics and virtual reality are integrated to create an effective environment for production assembly operators’ training. In this system virtual reality provides the grounds for realistic visualization, as well as immersion, whereas haptics enforces physical constraints within the virtual world generating the feelings of realistic interaction, making it accessible for formal learning and better understanding during task performance.

The developed research technology platform imitates real physical training scenarios by providing comprehensive user interaction, constrained within the physical limitations of the real world. Through the utilization of a haptics device, providing realistic force feedback, users are able to engage in product assembly training with a stronger sense of ‘reality’.

Realistic autonomous fish for virtual reality

We create realistic autonomous fish for Virtual Reality systems. The fish are realistic in appearance, movement and behaviour: the swimming behaviour being non-scripted, within real time rendering.The form of the fish is procedurally created. The size and shape of the form are controlled by a number of variables which are stored in a simple ASCII file. This allows efficient creation of different fish at run time.The behaviour is obtained by implementing a flocking algorithm.

3D sparse feature model using short baseline stereo and multiple view registration

This paper outlines a methodology to generate a distinctive object representation offline, using short-baseline stereo fundamentals to triangulate highly descriptive object features in multiple pairs of stereo images. A group of sparse 2.5D perspective views are built and the multiple views are then fused into a single sparse 3D model using a common 3D shape registration technique. Having prior knowledge, such as the proposed sparse feature model, is useful when detecting an object and estimating its pose for real-time systems like augmented reality.

Augmented optometry training simulator with multi-point haptics

Training of optometrists is traditionally achieved under close supervision of peers and superiors. With the rapid advancement in technology, medical procedures are performed more efficiently and effectively, resulting in faster recovery times and less trauma to the patient. However, application of this technology has made it difficult to effectively demonstrate and teach these manual skills as the education is now a combination of not only the medical procedure but also the use of the technology. In this paper we propose to increase the training capabilities of optometry students through haptically-enabled single-point and multi-point training tools as well as augmented reality techniques. Haptics technology allows a human to touch and feel virtual computer models as though they are real. Through physical connection to the operator, haptic devices are considered to be personal robots that are capable of improving the human-computer interaction with a virtual environment. These devices have played an increasing role in developing expertise, reducing instances of medical error and reducing training costs. A haptically-enabled virtual training environment, integrated with an optometry slit lamp instrument can be used to teach cognitive and manual skills while the system tracks the performance of each individual. These interactions would ideally replicate every aspect of the real procedure, consequently preparing the trainee for every possible scenario, without risking the health of a real patient.

Towards parameter-less 3D mesh segmentation

This thesis focuses on the 3D mesh segmentation process. The research demonstrated how the process can be done in a parameterless approach which allows full automation with accurate results. Applications of this research include, but not limited to, 3D search engines, 3D character animation, robotics environment recognition, and augmented reality.