EG 2017 - Short Papers

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https://diglib.eg.org/handle/10.2312/2631250

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Browsing EG 2017 - Short Papers by Subject "I.3.7 [Computer Graphics]"

Now showing 1 - 4 of 4
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    Detail Highlighting using a Shadow Edge Histogram
    (The Eurographics Association, 2017) Gkaravelis, Anastasios; Papaioannou, Georgios; Adrien Peytavie and Carles Bosch
    In this paper we propose a simple and effective technique for setting up a configuration of directional light sources to accentuate the prominent geometric features of complex objects by increasing the local shadow contrast near them. Practical applications of such a task are encountered among others in professional photography, and cinematography. The method itself, which is based on a voting mechanism, quickly produces consistent and view-independent results, with minimal user intervention.
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    Discovering New Monte Carlo Noise Filters with Genetic Programming
    (The Eurographics Association, 2017) Kán, Peter; Davletaliyev, Maxim; Kaufmann, Hannes; Adrien Peytavie and Carles Bosch
    This paper presents a novel method for the discovery of new analytical filters suitable for filtering of noise in Monte Carlo rendering. Our method utilizes genetic programming to evolve the set of analytical filtering expressions with the goal to minimize image error in training scenes. We show that genetic programming is capable of learning new filtering expressions with quality comparable to state of the art noise filters in Monte Carlo rendering. Additionally, the analytical nature of the resulting expressions enables the run-times one order of magnitude faster than compared state of the art methods. Finally, we present a new analytical filter discovered by our method which is suitable for filtering of Monte Carlo noise in diffuse scenes.
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    Parameter Estimation of BSSRDF for Heterogeneous Materials
    (The Eurographics Association, 2017) Sone, Hiroki; Hachisuka, Toshiya; Koike, Takafumi; Adrien Peytavie and Carles Bosch
    Rendering of highly scattering media is computationally expensive in general. While existing BSSRDF models can accurately and efficiently approximate light scattering in homogeneous media, we still have to resort to costly Monte Carlo simulation for heterogeneous media. We propose a simple parameter estimation method which enables homogeneous BSSRDF models to approximate the appearance of heterogeneous media. The main idea is to estimate the input optical parameters of a given homogeneous BSSRDF model such that the output well approximates light transport within heterogeneous media. Our method takes spatially varying optical coefficients into account by taking averages of the coefficients around the incident and exitant points. This approach is motivated by the path integral theory which predicts how wide the beam of light will spread in heterogeneous media. Since our method provides parameters for homogeneous BSSRDF models, it is applicable to many existing BSSRDF models and easy to integrate into existing rendering systems. We show that our modification produces more accurate results than the existing heuristics with the same goal.
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    Variable k-buffer using Importance Maps
    (The Eurographics Association, 2017) Vasilakis, Andreas-Alexandros; Vardis, Konstantinos; Papaioannou, Georgios; Moustakas, Konstantinos; Adrien Peytavie and Carles Bosch
    Successfully predicting visual attention can significantly improve many aspects of computer graphics and games. Despite the thorough investigation in this area, selective rendering has not addressed so far fragment visibility determination problems. To this end, we present the first ''selective multi-fragment rendering'' solution that alters the classic k-buffer construction procedure from a fixed-k to a variable-k per-pixel fragment allocation guided by an importance-driven model. Given a fixed memory budget, the idea is to allocate more fragment layers in parts of the image that need them most or contribute more significantly to the visual result. An importance map, dynamically estimated per frame based on several criteria, is used for the distribution of the fragment layers across the image. We illustrate the effectiveness and quality superiority of our approach in comparison to previous methods when performing order-independent transparency rendering in various, high depth-complexity, scenarios.