Volume 22, Number 2 (2014)
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Item Acquiring Bidirectional Texture Functions for Large-Scale Material Samples(Václav Skala - UNION Agency, 2014) Steinhausen, Heinz Christian; den Brok, Dennis; Hullin, Matthias B.; Klein, Reinhard; Skala, VáclavMost current acquisition setups for bidirectional texture functions (BTFs) are incapable of capturing large-scale material samples. We propose a method based on controlled texture synthesis to produce BTFs of appealing visual quality for such materials. Our approach uses as input data a complete measurement of a small fraction of the sample, together with few images of the large-scale structure controlling the synthesis process. We evaluate the applicability of our approach by reconstructing sparsified ground truth data and investigate the consequences of choosing different kinds and numbers of constraint images.
Item Patch-based sparse reconstruction of material BTFs(Václav Skala - UNION Agency, 2014) Brok, Dennis den; Steinhausen, Heinz Christian; Hullin, Matthias; Klein, Reinhard; Skala, VáclavWe propose a simple and efficient method to reconstruct materials’ bidirectional texture functions (BTFs) from angularly sparse measurements. The key observation is that materials of similar types exhibit both similar surface structure and reflectance properties. We exploit this by manually clustering an existing database of fully measured material BTFs and fitting a linear model to each of the clusters. The models are computed not on per-texel data but on small spatial BTF patches we call apparent BTFs. Sparse reconstruction can then be performed by solving a linear least-squares problem without any regularization, using a per-cluster sampling strategy derived from the models. We demonstrate that our method is capable of faithfully reconstructing fully resolved BTFs from sparse measurements for a wide range of materials.Item Cross-domain image matching improved by visual attention(Václav Skala - UNION Agency, 2014) de Melo, Ernani Viriato; de Amo, Sandra; Guliato, Denise; Skala, VáclavA good accuracy in image retrieval across different visual domains, such as photos taken over different seasons or lighting conditions, paintings, drawings, hand-drawn sketches, still is a big challenge. This paper proposes the use of visual attention to estimate the relative importance of some regions in a given query image. Recently, researchers used different databases in specific domains to validate their hypothesis. In this paper, we also propose a database with multiple image domains, called UFU-DDD. We used the UFU-DDD database to demonstrate the performance and accuracy gains from the association of visual attention with orientation-based feature descriptors. The analysis of the results showed that our approach outperforms all the standard descriptors used in the experiments. We hope the UFU-DDD database constitutes a valuable benchmark to the future research in cross-domain similarity searching.Item A Visuomotor Coordination Model for Obstacle Recognition(Václav Skala - UNION Agency, 2014) Iwao, Tomoyori; Kubo, Hiroyuki; Maejima, Akinobu; Morishima, Shigeo; Skala, VáclavIn this paper, we propose a novel method for animating CG characters that while walking or running pay heed to obstacles. Here, our primary contribution is to formulate a generic visuomotor coordination model for obstacle recognition with whole body movements. In addition, our model easily generates gaze shifts, which expresses the individuality of characters. Based on experimental evidence, we also incorporate the coordination of eye movements in response to obstacle recognition behavior via simple parameters related to the target position and individuality of the characters’s gaze shifts. Our overall model can generate plausible visuomotor coordinated movements in various scenes by manipulating parameters of our proposed functions.Item Improved Particle-based Ice Melting Simulation with SPH Air Model(Václav Skala - UNION Agency, 2014) Domaradzki, Jakub; Martyn, Tomasz; Skala, VáclavThis paper presents an improved method for simulating melting of ice. The melting process is implemented as a result of the heat transfer between ice objects and fluids (water and air). Both the solids and the fluids, including air, are modeled as a set of particles with specified temperatures, which can vary locally during simulation. The proposed new particle-based air model allows one to consider in simulation the influence of the natural air convection on the ice melting process. Moreover, the model makes it possible to melt the ice object in a controllable way by means of external heat sources. The motion of air and water, originally described by the Navier- Stokes equations for incompressible fluids, is computed using the Smoothed Particle Hydrodynamics (SPH) algorithm, which we modify to properly handle our particle-based air and its interactions with ice and water. Thanks to a GPU-based implementation, the proposed method allows us to run the simulation of ice melting at interactive speed on an average PC.
