A lower bound for the area of Plateau foams

Real foams can be viewed as geometrically well-organized dispersions of more or less spherical bubbles in a liquid. When the foam is so drained that the liquid content significantly decreases, the bubbles become polyhedral-like and the foam can be viewed now as a network of thin liquid films intersecting each other at the Plateau borders according to the celebrated Plateau’s laws. In this paper we estimate from below the surface area of a spherically bounded piece of a foam. Our main tool is a new version of the divergence theorem which is adapted to the specific geometry of a foam with special attention to its classical Plateau singularities. As a benchmark application of our results, we obtain lower bounds for the fundamental cell of a Kelvin foam, lower bounds for the so-called cost function, and for the difference of the pressures appearing in minimal periodic foams. Moreover, we provide an algorithm whose input is a set of isolated points in space and whose output is the best lower bound estimate for the area of a foam that contains the given set as its vertex set

Depth and All-in-Focus Image Estimation in Synthetic Aperture Integral Imaging Under Partial Occlusions

A common assumption in the integral imaging reconstruction is that a pixel will be photo-consistent if all viewpoints observed by the different cameras converge at a single point when focusing at the proper depth. However, the presence of occlusions between objects in the scene prevents this from being fulfilled. In this paper, a novel depth and all-in focus image estimation method is presented, based on a photo-consistency measure that uses the median criterion in relation to the elemental images. The interest of this approach is to find a solution to detect which camera correctly sees the partially occluded object at a certain depth and allows for a precise solution to the object depth. In addition, a robust solution is proposed to detect the boundary limits between partially occluded objects, which are subsequently used during the regularization depth estimation process. The experimental results show that the proposed method outperforms other state-of-the-art depth estimation methods in a synthetic aperture integral imaging framework

Analyzing autostereoscopic environment confgurations for the design of videogames

Stereoscopic devices are becoming more popular every day. The 3D visualization that these displays ofer is being used by videogame designers to enhance the user’s game experience. Autostereoscopic monitors ofer the possibility of obtaining this 3D visualization without the need for extra device. This fact makes them more attractive to videogame developers. However, the confguration of the cameras that make it possible to obtain an immersive 3D visualization inside the game is still an open problem. In this paper, some system confgurations that create autostereoscopic visualization in a 3D game engine were evaluated to obtain a good accommodation of the user experience with the game. To achieve this, user tests that take into account the movement of the player were carried out to evaluate diferent camera confgurations, namely, dynamic and static converging optical axis and parallel optical axis. The purpose of these tests is to evaluate the user experience regarding visual discomfort resulting from the movement of the objects, with the purpose of assessing the preference for one confguration or the other. The results show that the users tend to have a preference trend for the parallel optical axis confguration set. This confguration seems to be optimal because the area where the moving objects are focused is deeper than in the other confgurations

Depth Estimation in Integral Imaging Based on a Maximum Voting Strategy

An approach that uses the scene information acquired by means of a three-dimensional (3D) synthetic aperture integral imaging system is presented. This method generates a depth map of the scene through a voting strategy. In particular, we consider the information given by each camera of the array for each pixel, and also the local information in the neighbourhood of that pixel. The proposed method obtains consistent results for any type of object surfaces as well as very sharp boundaries. In addition, we also contribute in this paper with a repository of a set of synthetic integral images generated by 3DS Max where the so-called ground truth (real-true depth map) is available. This resource can be used as a benchmark to test any Integral Imaging based range estimation method.This work was supported in part by the Spanish Ministry of Economy and Competitiveness (MINECO) under the projects SEOSAT (ESP2013-48458-C4-3-P) and MTM2013-48371-C2-2-P, in part by the Generalitat Valenciana through the project PROMETEO-II-2014-062, and in part by the University Jaume I through the project UJI-P11B2014-09. The work of B. Javidi was supported by the National Science Foundation under Grant NSF/IIS-1422179

Synthetic content generation for auto-stereoscopic displays

Due to the appearance of auto-stereoscopic visualization as one of the most emerging tendencies used in displays, new content generation techniques for this kind of visualization are required. In this paper we present a study for the generation of multi-view synthetic content, studying several camera setups (planar, cylindrical and hyperbolic) and their configurations. We discuss the different effects obtained varying the parameters of these setups. A study with several users was made to analyze visual perceptions, asking them for their optimal visualization. To create the virtual content, a multi-view system has been integrated in a powerful game engine, which allows us to use the latest graphics hardware advances. This integration is detailed and several demos and videos are attached with this paper, which represent a virtual world for auto-stereoscopic displays and the same scenario in a two-view anaglyph representation for being visualized in any conventional display. In all these demos, the parameters studied can be modified offering the possibility of easily appreciate their effects in a virtual scene

Effect of Denoising in Band Selection for Regression Tasks in Hyperspectral Datasets

This paper presents a comparative analysis of six band selection methods applied to hyperspectral datasets for biophysical variable estimation problems, where the effect of denoising on band selection performance has also been analyzed. In particular, we consider four hyperspectral datasets and three regressors of different nature ("�SVR, Regression Trees, and Kernel Ridge Regression). Results show that the denoising approach improves the band selection quality of all the tested methods. We show that noise filtering is more beneficial for the selection methods that use an estimator based on the whole dataset for the prediction of the output than for methods that use strategies based on local information (neighboring points)

A game engine to make games as multi-agent systems

Video games are applications that present design patterns that resemble multi-agent systems. Game objects or actors are like autonomous agents that interact with each other to describe complex systems. The purpose of this work is to develop a game engine to build games as multi-agent systems. The actors or game engine agents have a set of properties and behaviour rules with the end to interact with the environment of the game. The behaviour definition is established through a formal semantic based on predicate logic. The proposed engine tries to fulfil the basic requirements of the multi-agent systems, by adjusting the characteristics of the system, without affecting its potential. Finally, a set of games are introduced to validate the operation and possibilities of the engine

Procedural modeling of plant ecosystems maximizing vegetation cover

Vegetation plays a major role in the realistic display of outdoor scenes. However, manual plant placement can be tedious. For this reason this paper presents a new proposal in the field of procedural modeling of natural scenes. This method creates plant ecosystems that maximizes the covered space by optimizing an objective function subject to a series of constraints defined by a system of inequalities. This system includes the constraints of the environment taking into account characteristics of the terrain and the plant species involved. Once the inequality system has been defined, a solution will be obtained that tries to maximize the radius of the projected area of the trees and therefore the extension of the vegetation cover on the ground. The technique eliminates the trees that do not achieve a minimum growth radius, simulating the typical competitive process of nature. Results show the good performance and the high visual quality of the ecosystems obtained by the proposed technique. The use of this kind of optimization techniques could be used to solve other procedural modeling problems in other fields of application.Funding for open access charge: CRUE-Universitat Jaume

Back propagation with balanced MSE cost Function and nearest neighbor editing for handling class overlap and class imbalance

The class imbalance problem has been considered a critical factor for designing and constructing the supervised classifiers. In the case of artificial neural networks, this complexity negatively affects the generalization process on under-represented classes. However, it has also been observed that the decrease in the performance attainable of standard learners is not directly caused by the class imbalance, but is also related with other difficulties, such as overlapping. In this work, a new empirical study for handling class overlap and class imbalance on multi-class problem is described. In order to solve this problem, we propose the joint use of editing techniques and a modified MSE cost function for MLP. This analysis was made on a remote sensing data . The experimental results demonstrate the consistency and validity of the combined strategy here proposedPartially supported by the Spanish Ministry of Education and Science under grants CSD2007–00018, TIN2009–14205–C04–04, and by Fundació Caixa Castelló–Bancaixa under grants P1–1B2009–04 and P1–1B2009–45; SDMAIA-010 of the TESJO and 2933/2010 from the UAE

Integral imaging techniques for flexible sensing through image-based reprojection

In this work, a 3D reconstruction approach for flexible sensing inspired by integral imaging techniques is proposed. This method allows the application of different integral imaging techniques, such as generating a depth map or the reconstruction of images on a certain 3D plane of the scene that were taken with a set of cameras located at unknown and arbitrary positions and orientations. By means of a photo-consistency measure proposed in this work, all-in-focus images can also be generated by projecting the points of the 3D plane into the sensor planes of the cameras and thereby capturing the associated RGB values. The proposed method obtains consistent results in real scenes with different surfaces of objects as well as changes in texture and lighting