LivePhantom: Retrieving Virtual World Light Data to Real Environments.

To achieve realistic Augmented Reality (AR), shadows play an important role in creating a 3D impression of a scene. Casting virtual shadows on real and virtual objects is one of the topics of research being conducted in this area. In this paper, we propose a new method for creating complex AR indoor scenes using real time depth detection to exert virtual shadows on virtual and real environments. A Kinect camera was used to produce a depth map for the physical scene mixing into a single real-time transparent tacit surface. Once this is created, the camera's position can be tracked from the reconstructed 3D scene. Real objects are represented by virtual object phantoms in the AR scene enabling users holding a webcam and a standard Kinect camera to capture and reconstruct environments simultaneously. The tracking capability of the algorithm is shown and the findings are assessed drawing upon qualitative and quantitative methods making comparisons with previous AR phantom generation applications. The results demonstrate the robustness of the technique for realistic indoor rendering in AR systems

Static scene illumination estimation from video with applications

We present a system that automatically recovers scene geometry and illumination from a video, providing a basis for various applications. Previous image based illumination estimation methods require either user interaction or external information in the form of a database. We adopt structure-from-motion and multi-view stereo for initial scene reconstruction, and then estimate an environment map represented by spherical harmonics (as these perform better than other bases). We also demonstrate several video editing applications that exploit the recovered geometry and illumination, including object insertion (e.g., for augmented reality), shadow detection, and video relighting

Shadow Generation in Augmented Reality: A Complete Survey

This paper provides an overview of the issues and techniques involved in shadow generation in mixed reality environments. Shadow generation techniques in virtual environments are explained briefly. The key factors characterizing the well-known techniques are described in detail and the pros and cons of each technique are discussed. The conceptual perspective, the improvements, and future techniques are also investigated, sum- marized, and analysed in depth. This paper aims to provide researchers with a solid background on the state- of-the-art implementation of shadows in mixed reality. Thus, this could make it easier to choose the most appropriate method to achieve the aims. It is also hoped that this analysis will help researchers find solutions to the problems facing each technique

Marker hiding methods: Applications in augmented reality

© 2015 Taylor & Francis Group, LLC.In augmented reality, the markers are noticeable by their simple design of a rectangular image with black and white areas that disturb the reality of the overall view. As the markerless techniques are not usually robust enough, hiding the markers has a valuable usage, which many researchers have focused on. Categorizing the marker hiding methods is the main motivation of this study, which explains each of them in detail and discusses the advantages and shortcomings of each. The main ideas, enhancements, and future works of the well-known techniques are also comprehensively summarized and analyzed in depth. The main goal of this study is to provide researchers who are interested in markerless or hiding-marker methods an easier approach for choosing the method that is best suited to their aims. This work reviews the different methods that hide the augmented reality marker by using information from its surrounding area. These methods have considerable differences in their smooth continuation of the textures that hide the marker area as well as their performance to hide the augmented reality marker in real time. It is also hoped that our analysis helps researchers find solutions to the drawbacks of each method. © 201