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Item Bidirectional Clustering for Scalable VPL-based Global Illumination(The Eurographics Association, 2015) Jarabo, Adrian; Buisan, Raul; Gutierrez, Diego; Mateu Sbert and Jorge Lopez-MorenoVirtual Point Lights (VPL) methods approximate global illumination (GI) in a scene by using a large number of virtual lights modeling the reflected radiance of a surface. These methods are efficient, and allow computing noise-free images significantly faster that other methods. However, they scale linearly with the number of virtual lights and with the number of pixels to be rendered. Previous approaches improve the scalability of the method by hierarchically evaluating the virtual lights, allowing sublinear performance with respect the lights being evaluated. In this work, we introduce a novel bidirectional clustering approach, by hierarchically evaluating both the virtual lights and the shading points. This allows reusing radiance evaluation between pixels, and obtaining sublinear costs with respect to both lights and camera samples. We demonstrate significantly better performance than state-of-the-art VPL clustering methods with several examples, including high-resolution images, distributed effects, and rendering of light fields.Item Structure-preserving Style Transfer(The Eurographics Association, 2019) Calvo, Santiago; Serrano, Ana; Gutierrez, Diego; Masia, Belen; Casas, Dan and Jarabo, AdriánTransferring different artistic styles to images while preserving their content is a difficult image processing task. Since the seminal deep learning approach of Gatys et al. [GEB16], many recent works have proposed different approaches for performing this task. However, most of them share one major limitation: a trade-off between how much the target style is transferred, and how much the content of the original source image is preserved [GEB16, GEB*17, HB17, LPSB17]. In this work, we present a structure-preserving approach for style transfer that builds on top of the approach proposed by Gatys et al. Our approach allows to preserve regions of fine detail by lowering the intensity of the style transfer for such regions, while still conveying the desired style in the overall appearance of the image. We propose to use a quad-tree image subdivision, and then apply the style transfer operation differently for different subdivision levels. Effectively, this leads to a more intense style transfer in large flat regions, while the content is better preserved in areas with fine structure and details. Our approach can be easily applied to different style transfer approaches as a post-processing step.Item Bidirectional Rendering of Polarized Light Transport(The Eurographics Association, 2016) Jarabo, Adrian; Gutierrez, Diego; Alejandro Garcia-Alonso and Belen MasiaOn the foundations of many rendering algorithm is the symmetry between the path traversed by light and its adjoint from the camera. However, several effects, including polarization or fluorescence, break that symmetry and are defined only on the direction of light. This complicates the applicability of bidirectional methods, that exploit the symmetry for effective rendering light transport. In this work we focus on how to include polarization within a bidirectional rendering algorithm. For that, we generalize the path integral to support the constraints imposed by non-symmetric light transport. Based on this theoretical framework, we propose modifications on two bidirectional methods, namely bidirectional path tracing and photon mapping, extending them to support polarization.Item Efficient Propagation of Light Field Edits(The Eurographics Association, 2021) Jarabo, Adrian; Masia, Belen; Gutierrez, Diego; Silva, F. and Gutierrez, D. and RodrÃguez, J. and Figueiredo, M.Light field editing is a complex task, due to the large amount of data and the need to keep consistency between views. This has hampered the creation of efficient edit propagation methods, similar to those existing for single images. We propose a framework to edit light fields at interactive rates, by propagating some sparse user edits in the full light field. This propagation is guided by a novel affinity function, which forces similar pixels (defined by our affinity space) to receive similar edits, thus ensuring consistency. To manage the light field's large amount of data, we propose a novel multi-dimensional downsampling technique: we first cluster pixels with high affinity, and then perform edit propagation over the downsampled data. We finally upsample back to the original full resolution, maintaining visual fidelity and view consistency between views.Item Low Cost Decomposition of Direct and Global Illumination in Real Scenes(The Eurographics Association, 2015) Garces, Elena; Martin, Fernando; Gutierrez, Diego; Mateu Sbert and Jorge Lopez-MorenoRecent advances in the field of computational light transport have made it possible to solve previously unsolvable problems thanks to incorporating new devices and techniques. One of these problems is the decomposition of the illumination into its local and global components in real scenes. Previous work has managed to perform such a decomposition by projecting several light patterns on a target scene and processing its captures. In this work we build on that approach and propose two novel contributions: first, a new interpolation method, which allows the decomposition of the light components from a single capture of the projected scene into the native resolution, without requiring down-sampling; second, we propose an implementation of the algorithm for a mobile platform.Item Coded Apertures for Defocus Deblurring(The Eurographics Association, 2021) Masia, Belen; Corrales, Adrian; Presa, Lara; Gutierrez, Diego; Silva, F. and Gutierrez, D. and RodrÃguez, J. and Figueiredo, M.The field of computational photography, and in particular the design and implementation of coded apertures, has yielded impressive results in the last years. Among their applications lies defocus deblurring, in which we focus in this paper. Following the approach of previous works, we obtain near-optimal coded apertures using a genetic algorithm and an existing quality metric. We perform both synthetic and real experiments, testing the performance of the apertures along the dimensions of depth, size and shape. We additionally explore non-binary apertures, usually overlooked in the literature, and perform a comparative analysis with their binary counterparts.Item Transient Photon Beams(The Eurographics Association, 2017) Marco, Julio; Jarosz, Wojciech; Gutierrez, Diego; Jarabo, Adrian; Fco. Javier Melero and Nuria PelechanoRecent advances on transient imaging and their applications have opened the necessity of forward models that allow precise generation and analysis of time-resolved light transport data. However, traditional steady-state rendering techniques are not suitable for computing transient light transport due to the aggravation of the inherent Monte Carlo variance over time. These issues are specially problematic in participating media, which demand high number of samples to achieve noise-free solutions. We address this problem by presenting the first photon-based method for transient rendering of participating media that performs density estimations on time-resolved precomputed photon maps. We first introduce the transient integral form of the radiative transfer equation into the computer graphics community, including transient delays on the scattering events. Based on this formulation we leverage the high density and parameterized continuity provided by photon beams algorithms to present a new transient method that allows to significantly mitigate variance and efficiently render participating media effects in transient state.Item Compressive High Speed Video Acquisition(The Eurographics Association, 2015) Serrano, Ana; Gutierrez, Diego; Masia, Belen; Mateu Sbert and Jorge Lopez-MorenoTraditional video capture is limited by the trade-off between spatial and temporal resolution. When capturing videos of high temporal resolution, the spatial resolutions decreases due to bandwidth limitations in the capture system. Achieving both high spatial and temporal resolution is only possible with highly specialized and very expensive hardware; although the bandwidth is higher, the same basic trade-off remains. In this paper, we make use of a single-shot, high-speed video capture system, in order to overcome this limitation. It is based on compressive sensing, and relies on dictionary learning for sparse video representation. This allows capturing a video sequence by coding the temporal information in a single frame, and then reconstructing the full video sequence from this single coded image. We perform an in-depth analysis of the parameters of influence in the system, providing insights for future developments of similar systems.Item A Physically-Based Spatio-Temporal Sky Model(The Eurographics Association, 2018) Guimera, David; Gutierrez, Diego; Jarabo, Adrián; GarcÃa-Fernández, Ignacio and Ureña, CarlosIn this work we present a physically-based optical model of the atmosphere, that takes into account the seasonal and geographic variation of its composition. Based on data from the atmospheric science literature, we build a highly detailed the composition of the atmosphere, and how it varies depending on the position of the observer, or the time of the year. Then, based on precise measurements of the optical properties of the components of the atmosphere, we map our model into a radiative model, which can be rendered in any existing volumetric renderer. We demonstrate our model in multispectral renders of daylight sky-domes, showing the changes in the appearance occurring when varying the season or location of the observer.Item Graph-Based Reflectance Segmentation(The Eurographics Association, 2021) Garces, Elena; Gutierrez, Diego; Lopez-Moreno, Jorge; Silva, F. and Gutierrez, D. and RodrÃguez, J. and Figueiredo, M.Most of the unsupervised image segmentation algorithms use just RGB color information in order to establish the similarity criteria between pixels in the image. This leads in many cases to a wrong interpretation of the scene since these criteria do not consider the physical interactions which give raise to of those RGB values (illumination, geometry, albedo) nor our perception of the scene. In this paper, we propose a novel criterion for unsupervised image segmentation which not only relies on color features, but also takes into account an approximation of the materials reflectance. By using a perceptually uniform color space, we apply our criterion to one of the most relevant state of the art segmentation techniques, showing its suitability for segmenting images into small and coherent clusters of constant reflectance. Furthermore, due to the wide adoption of such algorithm, we provide for the first time in the literature an evaluation of this technique under several scenarios and different configurations of its parameters. Finally, in order to enhance both the accuracy of the segmentation and the inner coherence of the clusters, we apply a series of image processing filters to the input image (median, mean-shift, bilateral), analyzing their effects in the segmentation process. Our results can be transferred to any image segmentation algorithm.