Teaching complex theoretical multi-step problems in ICT networking through 3D printing and augmented reality

This paper presents a pilot study rationale and research methodology using a mixed media visualisation (3D printing and Augmented Reality simulation) learning intervention to help students in an ICT degree represent theoretical complex multi-step problems without a corresponding real world physical analog model. This is important because these concepts are difficult to visualise without a corresponding mental model. The proposed intervention uses an augmented reality application programmed with free commercially available tools, tested through an action research methodology, to evaluate the effectiveness of the mixed media visualisation techniques to teach ICT students networking. Specifically, 3D models of network equipment will be placed in a field and then the augmented reality app can be used to observe packet traversal and routing between the different devices as data travels from the source to the destination. Outcomes are expected to be an overall improvement in final skill level for all students

A Novel Solution of Using Mixed Reality in Bowel and Oral and Maxillofacial Surgical Telepresence: 3D Mean Value Cloning algorithm

Background and aim: Most of the Mixed Reality models used in the surgical telepresence are suffering from discrepancies in the boundary area and spatial-temporal inconsistency due to the illumination variation in the video frames. The aim behind this work is to propose a new solution that helps produce the composite video by merging the augmented video of the surgery site and the virtual hand of the remote expertise surgeon. The purpose of the proposed solution is to decrease the processing time and enhance the accuracy of merged video by decreasing the overlay and visualization error and removing occlusion and artefacts. Methodology: The proposed system enhanced the mean value cloning algorithm that helps to maintain the spatial-temporal consistency of the final composite video. The enhanced algorithm includes the 3D mean value coordinates and improvised mean value interpolant in the image cloning process, which helps to reduce the sawtooth, smudging and discolouration artefacts around the blending region. Results: As compared to the state of the art solution, the accuracy in terms of overlay error of the proposed solution is improved from 1.01mm to 0.80mm whereas the accuracy in terms of visualization error is improved from 98.8% to 99.4%. The processing time is reduced to 0.173 seconds from 0.211 seconds. Conclusion: Our solution helps make the object of interest consistent with the light intensity of the target image by adding the space distance that helps maintain the spatial consistency in the final merged video.Comment: 27 page

Breaking the Screen: Interaction Across Touchscreen Boundaries in Virtual Reality for Mobile Knowledge Workers.

Virtual Reality (VR) has the potential to transform knowledge work. One advantage of VR knowledge work is that it allows extending 2D displays into the third dimension, enabling new operations, such as selecting overlapping objects or displaying additional layers of information. On the other hand, mobile knowledge workers often work on established mobile devices, such as tablets, limiting interaction with those devices to a small input space. This challenge of a constrained input space is intensified in situations when VR knowledge work is situated in cramped environments, such as airplanes and touchdown spaces. In this paper, we investigate the feasibility of interacting jointly between an immersive VR head-mounted display and a tablet within the context of knowledge work. Specifically, we 1) design, implement and study how to interact with information that reaches beyond a single physical touchscreen in VR; 2) design and evaluate a set of interaction concepts; and 3) build example applications and gather user feedback on those applications.Comment: 10 pages, 8 figures, ISMAR 202

Big Data Visualization Platform for Mixed Reality

The visualization of data helps to provide faster and deeper insight into the data. In this work, a system for visualizing and analyzing big data in an interactive mixed reality environment is proposed. Such a system can be used for representing different types of data such as temporal, geospatial, network graph, and high dimensional. Also, an implementation of this system for four different data types are created. The data types include network data, volumetric data, high dimensional, and spectral data for different mixed reality devices such as Microsoft HoloLens, Oculus Rift, Samsung Gear VR, and Android ARCore were created. It was shown that such a system could store and use billions of samples and represent millions of them at once