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Item EUROGRAPHICS 2016: Tutorials Frontmatter(Eurographics Association, 2016) Sousa, A. Augusto; Bouatouch, Kadi;Item Improving Performance and Accuracy of Local PCA(The Eurographics Association and Blackwell Publishing Ltd., 2011) Gassenbauer, Václav; Krivánek, Jaroslav; Bouatouch, Kadi; Bouville, Christian; Ribardière, Mickaël; Bing-Yu Chen, Jan Kautz, Tong-Yee Lee, and Ming C. LinLocal Principal Component Analysis (LPCA) is one of the popular techniques for dimensionality reduction and data compression of large data sets encountered in computer graphics. The LPCA algorithm is a variant of kmeans clustering where the repetitive classification of high dimensional data points to their nearest cluster leads to long execution times. The focus of this paper is on improving the efficiency and accuracy of LPCA. We propose a novel SortCluster LPCA algorithm that significantly reduces the cost of the point-cluster classification stage, achieving a speed-up of up to 20. To improve the approximation accuracy, we investigate different initialization schemes for LPCA and find that the k-means++ algorithm [AV07] yields best results, however at a high computation cost. We show that similar ideas that lead to the efficiency of our SortCluster LPCA algorithm can be used to accelerate k-means++. The resulting initialization algorithm is faster than purely random seeding while producing substantially more accurate data approximation.Item Automatic Aesthetics-based Lighting Design with Global Illumination(The Eurographics Association, 2014) Léon, Vincent; Gruson, Adrien; Cozot, Rémi; Bouatouch, Kadi; John Keyser and Young J. Kim and Peter WonkaIn computer graphics, lighting plays an important role in the appearance of a scene. A change in the configuration of light sources can lead to different aesthetics in the final rendered image. Lighting design becomes increasingly complex when using sophisticated global illumination techniques. In this paper, we present a new approach to automatically design the lighting configuration according to the aesthetic goal specified by the user as a set of target parameters. Target parameters are used to set up an objective function which is minimized using an optimization method. The results show that our method can be used to automatically design a lighting configuration that will give to the final image a classic photographic look.Item Bayesian and Quasi Monte Carlo Spherical Integration for Illumination Integrals(The Eurographics Association, 2014) Marques, Ricardo; Bouville, Christian; Bouatouch, Kadi; Nicolas Holzschuch and Karol MyszkowskiThe spherical sampling of the incident radiance function entails a high computational cost. Therefore the illumination integral must be evaluated using a limited set of samples. Such a restriction raises the question of how to obtain the most accurate approximation possible with such a limited set of samples. We need to ensure that sampling produces the highest amount of information possible by carefully placing the limited set of samples. Furthermore we want our integral evaluation to take into account not only the information produced by the sampling but also possible information available prior to sampling. In this tutorial we focus on the case of hemispherical sampling for spherical Monte Carlo (MC) integration. We will show that existing techniques can be improved by making a detailed analysis of the theory of MC spherical integration. We will then use this theory to identify and improve the weak points of current approaches, based on very recent advances in the fields of integration and spherical Quasi-Monte Carlo integration.Item Example‐Based Colour Transfer for 3D Point Clouds(© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2021) Goudé, Ific; Cozot, Rémi; Le Meur, Olivier; Bouatouch, Kadi; Benes, Bedrich and Hauser, HelwigExample‐based colour transfer between images, which has raised a lot of interest in the past decades, consists of transferring the colour of an image to another one. Many methods based on colour distributions have been proposed, and more recently, the efficiency of neural networks has been demonstrated again for colour transfer problems. In this paper, we propose a new pipeline with methods adapted from the image domain to automatically transfer the colour from a target point cloud to an input point cloud. These colour transfer methods are based on colour distributions and account for the geometry of the point clouds to produce a coherent result. The proposed methods rely on simple statistical analysis, are effective, and succeed in transferring the colour style from one point cloud to another. The qualitative results of the colour transfers are evaluated and compared with existing methods.Item Two-Level Adaptive Sampling for Illumination Integrals using Bayesian Monte Carlo(The Eurographics Association, 2016) Marques, Ricardo; Bouville, Christian; Santos, Luis P.; Bouatouch, Kadi; T. Bashford-Rogers and L. P. SantosBayesian Monte Carlo (BMC) is a promising integration technique which considerably broadens the theoretical tools that can be used to maximize and exploit the information produced by sampling, while keeping the fundamental property of data dimension independence of classical Monte Carlo (CMC). Moreover, BMC uses information that is ignored in the CMC method, such as the position of the samples and prior stochastic information about the integrand, which often leads to better integral estimates. Nevertheless, the use of BMC in computer graphics is still in an incipient phase and its application to more evolved and widely used rendering algorithms remains cumbersome. In this article we propose to apply BMC to a two-level adaptive sampling scheme for illumination integrals. We propose an efficient solution for the second level quadrature computation and show that the proposed method outperforms adaptive quasi-Monte Carlo in terms of image error and high frequency noise.Item Context-aware Clustering and Assessment of Photo Collections(Association for Computing Machinery, Inc (ACM), 2017) Kuzovkin, Dmitry; Pouli, Tania; Cozot, Rémi; Meur, Olivier Le; Kervec, Jonathan; Bouatouch, Kadi; Holger Winnemoeller and Lyn BartramTo ensure that all important moments of an event are represented and that challenging scenes are correctly captured, both amateur and professional photographers often opt for taking large quantities of photographs. As such, they are faced with the tedious task of organizing large collections and selecting the best images among similar variants. Automatic methods assisting with this task are based on independent assessment approaches, evaluating each image apart from other images in the collection. However, the overall quality of photo collections can largely vary due to user skills and other factors. In this work, we explore the possibility of contextaware image quality assessment, where the photo context is defined using a clustering approach, and statistics of both the extracted context and the entire photo collection are used to guide identification of low-quality photos. We demonstrate that our method is able to exibly adapt to the nature of processed albums and to facilitate the task of image selection in diverse scenarios.Item Style-aware Robust Color Transfer(The Eurographics Association, 2015) Hristova, Hristina; Meur, Olivier Le; Cozot, Rémi; Bouatouch, Kadi; Paul L. RosinTransferring features, such as light and colors, between input and reference images is the main objective of color transfer methods. Current state-of-the-art methods focus mainly on the complete transfer of the light and color distributions. However, they do not successfully grasp specific light and color variations in image styles. In this paper, we propose a local method for carrying out a transfer of style between two images. Our method partitions both images to Gaussian distributed clusters by considering their main style features. These features are automatically determined by the classification step of our algorithm. Moreover, we present several novel policies for input/reference cluster mapping, which have not been tackled so far by previous methods. To complete the style transfer, for each pair of corresponding clusters, we apply a parametric color transfer method and a local chromatic adaptation transform. Results, subjective user evaluation as well as objective evaluation show that the proposed method obtains visually pleasing and artifact-free images, respecting the reference style.Item Adaptive Records for Irradiance Caching(The Eurographics Association and Blackwell Publishing Ltd., 2011) Ribardière, Mickaël; Carré, Samuel; Bouatouch, Kadi; Eduard Groeller and Holly RushmeierIrradiance Caching is one of the most widely used algorithms to speed up global illumination. In this paper, we propose an algorithm based on the Irradiance Caching scheme that allows us (1) to adjust the density of cached records according to illumination changes and (2) to efficiently render the high‐frequency illumination changes. To achieve this, a new record footprint is presented. Although the original method uses records having circular footprints depending only on geometrical features, our record footprints have a more complex shape which accounts for both geometry and irradiance variations. Irradiance values are computed using a classical Monte Carlo ray tracing method that simplifies the determination of nearby objects and the pre‐computation of the shape of the influence zone of the current record. By gathering irradiance due to all the incident rays, illumination changes are evaluated to adjust the footprint’s records. As a consequence, the record footprints are smaller where illumination gradients are high. With this technique, the record density depends on the irradiance variations. Strong variations of irradiance (due to direct contributions for example) can be handled and evaluated accurately. Caching direct illumination is of high importance, especially in the case of scenes having many light sources with complex geometry as well as surfaces exposed to daylight. Recomputing direct illumination for the whole image can be very time‐consuming, especially for walkthrough animation rendering or for high‐resolution pictures. Storing such contributions in the irradiance cache seems to be an appropriate solution to accelerate the final rendering pass.Item Optimal Sample Weights for Hemispherical Integral Quadratures(© 2019 The Eurographics Association and John Wiley & Sons Ltd., 2019) Marques, Ricardo; Bouville, Christian; Bouatouch, Kadi; Chen, Min and Benes, BedrichThis paper proposes optimal quadrature rules over the hemisphere for the shading integral. We leverage recent work regarding the theory of quadrature rules over the sphere in order to derive a new theoretical framework for the general case of hemispherical quadrature error analysis. We then apply our framework to the case of the shading integral. We show that our quadrature error theory can be used to derive optimal sample weights (OSW) which account for both the features of the sampling pattern and the bidirectional reflectance distribution function (BRDF). Our method significantly outperforms familiar Quasi Monte Carlo (QMC) and stochastic Monte Carlo techniques. Our results show that the OSW are very effective in compensating for possible irregularities in the sample distribution. This allows, for example, to significantly exceed the regular convergence rate of stochastic Monte Carlo while keeping the exact same sample sets. Another important benefit of our method is that OSW can be applied whatever the sampling points distribution: the sample distribution need not follow a probability density function, which makes our technique much more flexible than QMC or stochastic Monte Carlo solutions. In particular, our theoretical framework allows to easily combine point sets derived from different sampling strategies (e.g. targeted to diffuse and glossy BRDF). In this context, our rendering results show that our approach overcomes MIS (Multiple Importance Sampling) techniques.This paper proposes optimal quadrature rules over the hemisphere for the shading integral. We leverage recent work regarding the theory of quadrature rules over the sphere in order to derive a new theoretical framework for the general case of hemispherical quadrature error analysis. We then apply our framework to the case of the shading integral. We show that our quadrature error theory can be used to derive optimal sample weights (OSW) which account for both the features of the sampling pattern and the material reflectance function (BRDF). Our method significantly outperforms familiar Quasi Monte Carlo (QMC) and stochastic Monte Carlo techniques. Our results show that the OSW are very effective in compensating for possible irregularities in the sample distribution. This allows, for example, to significantly exceed the regular convergence rate of stochastic Monte Carlo while keeping the exact same sample sets.