Carlos Aliaga

Special Section on Advanced Displays: Display adaptive 3D content remapping

Glasses-free automultiscopic displays are on the verge of becoming a standard technology in consumer products. These displays are capable of producing the illusion of 3D content without the need of any additional eyewear. However, due to limitations in angular resolution, they can only show a limited depth of field, which translates into blurred-out areas whenever an object extrudes beyond a certain depth. Moreover, the blurring is device-specific, due to the different constraints of each display. We introduce a novel display-adaptive light field retargeting method, to provide high-quality, blur-free viewing experiences of the same content on a variety of display types, ranging from hand-held devices to movie theaters. We pose the problem as an optimization, which aims at modifying the original light field so that the displayed content appears sharp while preserving the original perception of depth. In particular, we run the optimization on the central view and use warping to synthesize the rest of the light field. We validate our method using existing objective metrics for both image quality (blur) and perceived depth. The proposed framework can also be applied to retargeting disparities in stereoscopic image displays, supporting both dichotomous and non-dichotomous comfort zones.

To stylize or not to stylize?: the effect of shape and material stylization on the perception of computer-generated faces

Virtual characters contribute strongly to the entire visuals of 3D animated films. However, designing believable characters remains a challenging task. Artists rely on stylization to increase appeal or expressivity, exaggerating or softening specific features. In this paper we analyze two of the most influential factors that define how a character looks: shape and material. With the help of artists, we design a set of carefully crafted stimuli consisting of different stylization levels for both parameters, and analyze how different combinations affect the perceived realism, appeal, eeriness, and familiarity of the characters. Moreover, we additionally investigate how this affects the perceived intensity of different facial expressions (sadness, anger, happiness, and surprise). Our experiments reveal that shape is the dominant factor when rating realism and expression intensity, while material is the key component for appeal. Furthermore our results show that realism alone is a bad predictor for appeal, eeriness, or attractiveness.

A Biophysically-Based Model of the Optical Properties of Skin Aging

This paper presents a time‐varying, multi‐layered biophysically‐based model of the optical properties of human skin, suitable for simulating appearance changes due to aging. We have identified the key aspects that cause such changes, both in terms of the structure of skin and its chromophore concentrations, and rely on the extensive medical and optical tissue literature for accurate data. Our model can be expressed in terms of biophysical parameters, optical parameters commonly used in graphics and rendering (such as spectral absorption and scattering coefficients), or more intuitively with higher‐level parameters such as age, gender, skin care or skin type. It can be used with any rendering algorithm that uses diffusion profiles, and it allows to automatically simulate different types of skin at different stages of aging, avoiding the need for artistic input or costly capture processes. While the presented skin model is inspired on tissue optics studies, we also provided a simplified version valid for non‐diagnostic applications.

Sackcloth or silk?: the impact of appearance vs dynamics on the perception of animated cloth

Physical simulation and rendering of cloth is widely used in 3D graphics applications to create realistic and compelling scenes. However, cloth animation can be slow to compute and difficult to specify. In this paper, we present a set of experiments in which we explore some factors that contribute to the perception of cloth, to determine how efficiency could be improved without sacrificing realism. Using real video footage of several fabrics covering a wide range of visual appearances and dynamic behaviors, and their simulated counterparts, we explore the interplay of visual appearance and dynamics in cloth animation.

Perceptually-optimized content remapping for automultiscopic displays

3D content and display technology is now widely available. However, available displays range from large-screen cinematic projection systems to hand-held devices and from screens supporting glasses-free 3D modes to glasses-bound systems. Counterintuitively, the produced content is usually only generated for a single display configuration, making labor-intense, manual post-processing of the data necessary. Recently, several content remapping techniques for stereo content have been proposed (see e.g. [Lang et al. 2010]). We present a perceptually-driven optimization framework for automatic light field remapping, specially designed for automultiscopic displays. It takes into account both the limitations of the target display as well as those of a human observer, and poses the problem as a non-linear least squares optimization. Our model includes depth of field limitations and the contrast sensitivity function, as well as sensitivities to binocular disparity and motion parallax in the perception of depth. Additionally, the model can be adapted for more common stereo remapping.

A Radiative Transfer Framework for Spatially Correlated Materials

We introduce a non-exponential radiative framework that takes into account the local spatial correlation of scattering particles in a medium. Most previous works in graphics have ignored this, assuming uncorrelated media with a uniform, random local distribution of particles. However, positive and negative correlation lead to slower- and faster-than-exponential attenuation respectively, which cannot be predicted by the Beer-Lambert law. As our results show, this has a major effect on extinction, and thus appearance. From recent advances in neutron transport, we first introduce our Extended Generalized Boltzmann Equation, and develop a general framework for light transport in correlated media. We lift the limitations of the original formulation, including an analysis of the boundary conditions, and present a model suitable for computer graphics, based on optical properties of the media and statistical distributions of scatterers. In addition, we present an analytic expression for transmittance in the case of positive correlation, and show how to incorporate it efficiently into a Monte Carlo renderer. We show results with a wide range of both positive and negative correlation, and demonstrate the differences compared to classic light transport.

Mixed illumination analysis in single image for interactive color grading

Colorists often use keying or rotoscoping tools to access and edit particular colors or parts of the scene. Although necessary, this is a time-consuming and potentially imprecise process, as it is not possible to fully separate the influence of light sources in the scene from the colors of objects and actors within it. To simplify this process, we present a new solution for automatically estimating the color and influence of multiple illuminants, based on image variation analysis. Using this information, we present a new color grading tool for simply and interactively editing the colors of detected illuminants, which fits naturally in color grading workflows. We demonstrate the use of our solution in several scenes, evaluating the quality of our results by means of a psychophysical study.

A fiber-level model for predictive cloth rendering

Rendering realistic fabrics is an active research area with many applications in computer graphics and other fields like textile design. Reproducing the appearance of cloth remains challenging due to the micro-structures found in textiles, and the complex light scattering patterns exhibited at such scales. Recent approaches have reached very realistic results, either by directly modeling the arrangement of the fibers [Schröder et al. 2011], or capturing the structure of small pieces of cloth using Computed Tomography scanners (CT) [Zhao et al. 2011]. However, there is still a need for predictive modeling of cloth appearance; existing methods either rely on manually-set parameter values, or use photographs of real pieces of cloth to guide appearance matching algorithms, often assuming certain simplifications such as considering circular or elliptical cross sections, or assuming an homogeneous volume density, that lead to very different appearances.