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

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

Real-time Illumination and Visual Coherence for Photorealistic Augmented/Mixed Reality

A realistically inserted virtual object in the real-time physical environment is a desirable feature in augmented reality (AR) applications and mixed reality (MR) in general. This problem is considered a vital research area in computer graphics, a field that is experiencing ongoing discovery. The algorithms and methods used to obtain dynamic and real-time illumination measurement, estimating, and rendering of augmented reality scenes are utilized in many applications to achieve a realistic perception by humans. We cannot deny the powerful impact of the continuous development of computer vision and machine learning techniques accompanied by the original computer graphics and image processing methods to provide a significant range of novel AR/MR techniques. These techniques include methods for light source acquisition through image-based lighting or sampling, registering and estimating the lighting conditions, and composition of global illumination. In this review, we discussed the pipeline stages with the details elaborated about the methods and techniques that contributed to the development of providing a photo-realistic rendering, visual coherence, and interactive real-time illumination results in AR/MR

U-DiVE: Design and evaluation of a distributed photorealistic virtual reality environment

This dissertation presents a framework that allows low-cost devices to visualize and interact with photorealistic scenes. To accomplish this task, the framework makes use of Unity’s high-definition rendering pipeline, which has a proprietary Ray Tracing algorithm, and Unity’s streaming package, which allows an application to be streamed within its editor. The framework allows the composition of a realistic scene using a Ray Tracing algorithm, and a virtual reality camera with barrel shaders, to correct the lens distortion needed for the use on an inexpensive cardboard. It also includes a method to collect the mobile device’s spatial orientation through a web browser to control the user’s view, delivered via WebRTC. The proposed framework can produce low-latency, realistic and immersive environments to be accessed through low-cost HMDs and mobile devices. To evaluate the structure, this work includes the verification of the frame rate achieved by the server and mobile device, which should be higher than 30 FPS for a smooth experience. In addition, it discusses whether the overall quality of experience is acceptable by evaluating the delay of image delivery from the server up to the mobile device, in face of user’s movement. Our tests showed that the framework reaches a mean latency around 177 (ms) with household Wi-Fi equipment and a maximum latency variation of 77.9 (ms), among the 8 scenes tested.Esta dissertação apresenta um framework que permite que dispositivos de baixo custo visualizem e interajam com cenas fotorrealísticas. Para realizar essa tarefa, o framework faz uso do pipeline de renderização de alta definição do Unity, que tem um algoritmo de rastreamento de raio proprietário, e o pacote de streaming do Unity, que permite o streaming de um aplicativo em seu editor. O framework permite a composição de uma cena realista usando um algoritmo de Ray Tracing, e uma câmera de realidade virtual com shaders de barril, para corrigir a distorção da lente necessária para usar um cardboard de baixo custo. Inclui também um método para coletar a orientação espacial do dispositivo móvel por meio de um navegador Web para controlar a visão do usuário, entregue via WebRTC. O framework proposto pode produzir ambientes de baixa latência, realistas e imersivos para serem acessados por meio de HMDs e dispositivos móveis de baixo custo. Para avaliar a estrutura, este trabalho considera a verificação da taxa de quadros alcançada pelo servidor e pelo dispositivo móvel, que deve ser superior a 30 FPS para uma experiência fluida. Além disso, discute se a qualidade geral da experiência é aceitável, ao avaliar o atraso da entrega das imagens desde o servidor até o dispositivo móvel, em face da movimentação do usuário. Nossos testes mostraram que o framework atinge uma latência média em torno dos 177 (ms) com equipamentos wi-fi de uso doméstico e uma variação máxima das latências igual a 77.9 (ms), entre as 8 cenas testadas

SPA: Sparse Photorealistic Animation using a single RGB-D camera

Photorealistic animation is a desirable technique for computer games and movie production. We propose a new method to synthesize plausible videos of human actors with new motions using a single cheap RGB-D camera. A small database is captured in a usual office environment, which happens only once for synthesizing different motions. We propose a markerless performance capture method using sparse deformation to obtain the geometry and pose of the actor for each time instance in the database. Then, we synthesize an animation video of the actor performing the new motion that is defined by the user. An adaptive model-guided texture synthesis method based on weighted low-rank matrix completion is proposed to be less sensitive to noise and outliers, which enables us to easily create photorealistic animation videos with new motions that are different from the motions in the database. Experimental results on the public dataset and our captured dataset have verified the effectiveness of the proposed method