Digital games as education tools for children have been studied in the past. However, the use of digital games in clinical environments such as for children's healthcare is still rare in the research community. This paper reports on the development of a digital tablet game called "Dodo's catching adventure" which examines the use of games in visual colordeficiency screening for young children. A user study was conducted at a National Eye Centre. Results of the study show that the digital game demonstrates sensitivity and specificity on RedGreen color deficiency detection, and is comparable to the two gold standards in color deficiency tests, namely the Ishihara and Farnsworth D15. Furthermore, children found the game to be more enjoyable than the Ishihara test. This provides evidence for the feasibility of using such games as diagnosis tools for early childhood health conditions.

Goal-oriented visual search is performed when a person intentionally seeks a target in the visual environment. In augmented reality (AR) environments, visual search can be facilitated by augmenting virtual cues in the person's field of view. Traditional use of explicit AR cues can potentially degrade visual search performance due to the creation of distortions in the scene. An alternative to explicit cueing, known as subtle cueing, has been proposed as a clutter-neutral method to enhance visual search in video-see-through AR. However, the effects of subtle cueing are still not well understood, and more research is required to determine the optimal methods of applying subtle cueing in AR. We performed two experiments to investigate the variables of scene clutter, subtle cue opacity, size, and shape on visual search performance. We introduce a novel method of experimentally manipulating the scene clutter variable in a natural scene while controlling for other variables. The findings provide supporting evidence for the subtlety of the cue, and show that the clutter conditions of the scene can be used both as a global classifier, as well as a local performance measure.

Goal-oriented visual search in augmented reality can be facilitated by using visual cues to call attention to a target. However, traditional use of explicit cues can degrade visual search performance due to scene distortion, occlusion and addition of visual clutter. In contrast, Subtle Cueing has been previously proposed as an alter-native to explicit cueing, but little is known about how well it works for head-tracked head worn displays (HWDs). We investigated the effect of Subtle Cueing for head-tracked head worn displays, using visual search research methods in simulated augmented reality environments. Our user study found that Subtle Cueing improves visual search performance, and serves as a feasible cueing mechanism for AR environments using HWDs.

Visual search in augmented reality environments is an important task that can be facilitated through different cueing methods. Current cueing methods rely on explicit cueing, which can potentially reduce visual search performance. In comparison, this paper proposes a subtle cueing method that improves visual search performance while being clutter-neutral. Two empirical user studies were conducted to evaluate our subtle cueing method in outdoor scenes. The results show that subtle cueing functions well within a narrow Feature Congestion range, and could be a feasible alternative to explicit cueing.

In this paper we present a novel model-based hybrid technique for user localization and drift-free tracking in urban environments. In outdoor augmented reality, instantaneous 6-DoF user localization is achieved with position and orientation sensors such as GPS and gyroscopes. Initial pose obtained with these sensors is dominated by large positional errors due to coarse granularity of GPS data. Subsequent tracking is also erroneous as gyroscopes are prone to drifts and often need recalibration. We propose to use model-to-image registration technique to refine initial rough estimate for accurate user localization. Large positional errors in user localization are mitigated by aligning silhouettes of the model with that of the camera image using shape context descriptors as they are invariant to translation, scale and rotational errors. Once initialized, drift-free tracking is achieved by combining frame-to-frame and model-to-frame feature tracking. Frame-to-frame tracking is done by matching corners whereas edges are used for model-to-frame silhouette tracking. Final camera pose is obtained with M-estimators.

This paper presents a novel approach for user positioning, robust tracking and online 3D mapping for outdoor augmented reality applications. As coarse user pose obtained from GPS and orientation sensors is not sufficient for augmented reality applications, sub-meter accurate user pose is then estimated by a one-step silhouette matching approach. Silhouette matching of the rendered 3D model and camera data is carried out with shape context descriptors as they are invariant to translation, scale and rotational errors, giving rise to a non-iterative registration approach. Once the user is correctly positioned, further tracking is carried out with camera data alone. Drifts associated with vision based approaches are minimized by combining different feature modalities. Robust visual tracking is maintained by fusing frame-to-frame and model-to-frame feature matches. Frame-to-frame tracking is accomplished with corner matching while edges are used for model-to-frame registration. Results from individual feature tracker are fused using a pose estimate obtained from an extended Kalman filter (EKF) and a weighted M-estimator. In scenarios where dense 3D models of the environment are not available, online 3D incremental mapping and tracking is proposed to track the user in unprepared environments. Incremental mapping prepares the 3D point cloud of the outdoor environment for tracking.

During times of calamity, such as an earthquake or tsunami, rescue and recovery efforts are usually hampered by communications failure as the incumbent communications infrastructure has most likely been damaged or destroyed during the disaster. An ad-hoc communications infrastructure, with support for multimedia traffic such as Voice over IP and video- streaming, must be quickly put in place to support the command, control and communication needs of the rescue and recovery operations. Such applications require relatively fast and robust communications links, and broadband wireless technologies appear to be a viable solution. This paper examines two hierarchical network solutions which allow the delivery of such mission-critical multimedia data between rescue teams and their headquarters over extremely long distances using a combination of wireless network technologies (namely, WiFi, WiMax and GEO Satellite) and multimedia software applications (in particular, Voice-over-IP) to meet the requirements of disaster rescue communication scenarios. The proposed system has been validated experimentally in the field as well as using simulations to demonstrate the scalability of the design.