31,846 research outputs found
A New Calibration Process for a Homogeneous Cyclorama Illumination in Virtual TV Sets
A virtual TV set combines actors and objects with computer-generated virtual environments in real time. Nowadays, this technology is widely used in television broadcasts and cinema productions. A virtual TV set consists of three main elements: the stage, the computer-system and the chroma-keyer. The stage is composed by a monochrome cyclorama (the background) in front of which actors and objects are located (the foreground). The computer-system generates the virtual elements that will form the virtual environment. The chroma-keyer combines the elements in the foreground with the computer-generated environments by erasing the monochrome background and insetting the synthetic elements using the chroma-keying technique. In order to ease the background removal, the cyclorama illumination must be diffuse and homogeneous, avoiding the hue differences that are introduced by shadows, shines and over-lighted areas. The analysis of this illumination is usually performed manually by an expert using a photometer which makes the process slow, tedious and dependent on the experience of the operator. In this paper, a new calibration process to check and improve the homogeneity of a cyclorama’s illumination by non-experts using a custom software which provides both visual information and statistical data, is presented. This calibration process segments a cyclorama image in regions with similar luminance and calculates the centroid of each of them. The statistical study of the variation in the size of the regions and the position of the centroids are the key tools used to determine the homogeneity of the cyclorama lighting.This work has received financial support from the Consellería de Cultura, Educación e Ordenación Universitaria (accreditation 2016–2019, ED431G/08) and the European Regional Development Fund (ERDF)S
Developing serious games for cultural heritage: a state-of-the-art review
Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result, the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented
Serious Games in Cultural Heritage
Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented
How to Train a CAT: Learning Canonical Appearance Transformations for Direct Visual Localization Under Illumination Change
Direct visual localization has recently enjoyed a resurgence in popularity
with the increasing availability of cheap mobile computing power. The
competitive accuracy and robustness of these algorithms compared to
state-of-the-art feature-based methods, as well as their natural ability to
yield dense maps, makes them an appealing choice for a variety of mobile
robotics applications. However, direct methods remain brittle in the face of
appearance change due to their underlying assumption of photometric
consistency, which is commonly violated in practice. In this paper, we propose
to mitigate this problem by training deep convolutional encoder-decoder models
to transform images of a scene such that they correspond to a previously-seen
canonical appearance. We validate our method in multiple environments and
illumination conditions using high-fidelity synthetic RGB-D datasets, and
integrate the trained models into a direct visual localization pipeline,
yielding improvements in visual odometry (VO) accuracy through time-varying
illumination conditions, as well as improved metric relocalization performance
under illumination change, where conventional methods normally fail. We further
provide a preliminary investigation of transfer learning from synthetic to real
environments in a localization context. An open-source implementation of our
method using PyTorch is available at https://github.com/utiasSTARS/cat-net.Comment: In IEEE Robotics and Automation Letters (RA-L) and presented at the
IEEE International Conference on Robotics and Automation (ICRA'18), Brisbane,
Australia, May 21-25, 201
Joint Material and Illumination Estimation from Photo Sets in the Wild
Faithful manipulation of shape, material, and illumination in 2D Internet
images would greatly benefit from a reliable factorization of appearance into
material (i.e., diffuse and specular) and illumination (i.e., environment
maps). On the one hand, current methods that produce very high fidelity
results, typically require controlled settings, expensive devices, or
significant manual effort. To the other hand, methods that are automatic and
work on 'in the wild' Internet images, often extract only low-frequency
lighting or diffuse materials. In this work, we propose to make use of a set of
photographs in order to jointly estimate the non-diffuse materials and sharp
lighting in an uncontrolled setting. Our key observation is that seeing
multiple instances of the same material under different illumination (i.e.,
environment), and different materials under the same illumination provide
valuable constraints that can be exploited to yield a high-quality solution
(i.e., specular materials and environment illumination) for all the observed
materials and environments. Similar constraints also arise when observing
multiple materials in a single environment, or a single material across
multiple environments. The core of this approach is an optimization procedure
that uses two neural networks that are trained on synthetic images to predict
good gradients in parametric space given observation of reflected light. We
evaluate our method on a range of synthetic and real examples to generate
high-quality estimates, qualitatively compare our results against
state-of-the-art alternatives via a user study, and demonstrate
photo-consistent image manipulation that is otherwise very challenging to
achieve
Feeling crowded yet?: Crowd simulations for VR
With advances in virtual reality technology and its multiple applications, the need for believable, immersive virtual environments is increasing. Even though current computer graphics methods allow us to develop highly realistic virtual worlds, the main element failing to enhance presence is autonomous groups of human inhabitants. A great
number of crowd simulation techniques have emerged in the last decade, but critical details in the crowd's movements and appearance do not meet the standards necessary to convince VR participants that they are present in a real crowd. In this paper, we review recent advances in the creation of immersive virtual crowds and discuss areas that require further work to turn these simulations into more fully immersive and believable experiences.Peer ReviewedPostprint (author's final draft
- …