An automated calibration method for non-see-through head mounted displays

Accurate calibration of a head mounted display (HMD) is essential both for research on the visual system and for realistic interaction with virtual objects. Yet, existing calibration methods are time consuming and depend on human judgements, making them error prone, and are often limited to optical see-through HMDs. Building on our existing approach to HMD calibration Gilson et al. (2008), we show here how it is possible to calibrate a non-see-through HMD. A camera is placed inside a HMD displaying an image of a regular grid, which is captured by the camera. The HMD is then removed and the camera, which remains fixed in position, is used to capture images of a tracked calibration object in multiple positions. The centroids of the markers on the calibration object are recovered and their locations re-expressed in relation to the HMD grid. This allows established camera calibration techniques to be used to recover estimates of the HMD display's intrinsic parameters (width, height, focal length) and extrinsic parameters (optic centre and orientation of the principal ray). We calibrated a HMD in this manner and report the magnitude of the errors between real image features and reprojected features. Our calibration method produces low reprojection errors without the need for error-prone human judgements

Dynamic Illumination for Augmented Reality with Real-Time Interaction

Current augmented and mixed reality systems suffer a lack of correct illumination modeling where the virtual objects render the same lighting condition as the real environment. While we are experiencing astonishing results from the entertainment industry in multiple media forms, the procedure is mostly accomplished offline. The illumination information extracted from the physical scene is used to interactively render the virtual objects which results in a more realistic output in real-time. In this paper, we present a method that detects the physical illumination with dynamic scene, then uses the extracted illumination to render the virtual objects added to the scene. The method has three steps that are assumed to be working concurrently in real-time. The first is the estimation of the direct illumination (incident light) from the physical scene using computer vision techniques through a 360° live-feed camera connected to AR device. The second is the simulation of indirect illumination (reflected light) from the real-world surfaces to virtual objects rendering using region capture of 2D texture from the AR camera view. The third is defining the virtual objects with proper lighting and shadowing characteristics using shader language through multiple passes. Finally, we tested our work with multiple lighting conditions to evaluate the accuracy of results based on the shadow falling from the virtual objects which should be consistent with the shadow falling from the real objects with a reduced performance cost

Application of augmented reality and robotic technology in broadcasting: A survey

As an innovation technique, Augmented Reality (AR) has been gradually deployed in the broadcast, videography and cinematography industries. Virtual graphics generated by AR are dynamic and overlap on the surface of the environment so that the original appearance can be greatly enhanced in comparison with traditional broadcasting. In addition, AR enables broadcasters to interact with augmented virtual 3D models on a broadcasting scene in order to enhance the performance of broadcasting. Recently, advanced robotic technologies have been deployed in a camera shooting system to create a robotic cameraman so that the performance of AR broadcasting could be further improved, which is highlighted in the paper

VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera

We present the first real-time method to capture the full global 3D skeletal pose of a human in a stable, temporally consistent manner using a single RGB camera. Our method combines a new convolutional neural network (CNN) based pose regressor with kinematic skeleton fitting. Our novel fully-convolutional pose formulation regresses 2D and 3D joint positions jointly in real time and does not require tightly cropped input frames. A real-time kinematic skeleton fitting method uses the CNN output to yield temporally stable 3D global pose reconstructions on the basis of a coherent kinematic skeleton. This makes our approach the first monocular RGB method usable in real-time applications such as 3D character control---thus far, the only monocular methods for such applications employed specialized RGB-D cameras. Our method's accuracy is quantitatively on par with the best offline 3D monocular RGB pose estimation methods. Our results are qualitatively comparable to, and sometimes better than, results from monocular RGB-D approaches, such as the Kinect. However, we show that our approach is more broadly applicable than RGB-D solutions, i.e. it works for outdoor scenes, community videos, and low quality commodity RGB cameras.Comment: Accepted to SIGGRAPH 201

A Modular Approach to the Development of Interactive Augmented Reality Applications.

Augmented reality (AR) technologies are becoming increasingly popular as a result of the increase in the power of mobile computing devices. Emerging AR applications have the potential to have an enormous impact on industries such as education, healthcare, research, training and entertainment. There are currently a number of augmented reality toolkits and libraries available for the development of these applications; however, there is currently no standard tool for development. In this thesis we propose a modular approach to the organization and development of AR systems in order to enable the creation novel AR experiences. We also investigate the incorporation of the framework that resulted from our approach into game engines to enable the creation and visualization of immersive virtual reality experiences. We address issues in the development process of AR systems and provide a solution for reducing the time, cost and barrier of entry for development while simultaneously providing a framework in which researchers can test and apply advanced augmented reality technologies

Piloting mobile mixed reality simulation in paramedic distance education

New pedagogical methods delivered through mobile mixed reality (via a user-supplied mobile phone incorporating 3d printing and augmented reality) are becoming possible in distance education, shifting pedagogy from 2D images, words and videos to interactive simulations and immersive mobile skill training environments. This paper presents insights from the implementation and testing of a mobile mixed reality intervention in an Australian distance paramedic science classroom. The context of this mobile simulation study is skills acquisition in airways management focusing on direct laryngoscopy with foreign body removal. The intervention aims to assist distance education learners in practicing skills prior to attending mandatory residential schools and helps build a baseline equality between those students that study face to face and those at a distance. Outcomes from the pilot study showed improvements in several key performance indicators in the distance learners, but also demonstrated problems to overcome in the pedagogical method

Toward Real-Time Video-Enhanced Augmented Reality for Medical Visualization and Simulation

In this work we demonstrate two separate forms of augmented reality environments for use with minimally-invasive surgical techniques. In Chapter 2 it is demonstrated how a video feed from a webcam, which could mimic a laparoscopic or endoscopic camera used during an interventional procedure, can be used to identify the pose of the camera with respect to the viewed scene and augment the video feed with computer-generated information, such as rendering of internal anatomy not visible beyond the image surface, resulting in a simple augmented reality environment. Chapter 3 details our implementation of a similar system to the one previously mentioned, albeit with an external tracking system. Additionally, we discuss the challenges and considerations for expanding this system to support an external tracking system, specifically the Polaris Spectra optical tracker. Because of the relocation of the tracking origin to a point other than the camera center, there is an additional registration step necessary to establish the position of all components within the scene. This modification is expected to increase accuracy and robustness of the system