A new robust algorithmic for multi-camera calibration with a 1D object under general motions without prior knowledge of any camera intrinsic parameter

In computer vision, camera calibration is a necessary process when the retrieval of information such as angles and distances is required. This paper addresses the multi-camera calibration problem with a single dimension calibration pattern under general motions. Currently, the known algorithms for solving this problem are based on the estimation of vanishing points. However, this estimate is very susceptible to noise, making the methods unsuitable for practical applications. Instead, this paper presents a new calibration algorithm, where the cameras are divided into binocular sets. The fundamental matrix of each binocular set is then estimated, allowing to perform a projective calibration of each camera. Then, the calibration is updated for the Euclidean space, ending the process. The calibration is possible without imposing any restrictions on the movement of the pattern and without any prior information about the cameras or motion. Experiments on synthetic and real images validate the new method and show that its accuracy makes it suitable also for practical applications.     

A case study on business process recovery using an e‐government system

Business processes have become one of the key assets of organization, since these processes allow them to discover and control what occurs in their environments, with information systems automating most of an organization's processes. Unfortunately, and as a result of uncontrolled maintenance, information systems age over time until it is necessary to replace them with new and modernized systems. However, while systems are aging, meaningful business knowledge that is not present in any of the organization's other assets gradually becomes embedded in them. The preservation of this knowledge through the recovery of the underlying business processes is, therefore, a critical problem. This paper provides, as a solution to the aforementioned problem, a model‐driven procedure for recovering business processes from legacy information systems. The procedure proposes a set of models at different abstraction levels, along with the model transformations between them. The paper also provides a supporting tool, which facilitates its adoption. Moreover, a real‐life case study concerning an e‐government system applies the proposed recovery procedure to validate its effectiveness and efficiency. The case study was carried out by following a formal protocol to improve its rigor and replicability. Copyright © 2011 John Wiley & Sons, Ltd.     

Progressive Virtual Beam Lights

A recent technique that forms virtual ray lights (VRLs) from path segments in media, reduces the artifacts common to VPL approaches in participating media, however, distracting singularities still remain. We present Virtual Beam Lights (VBLs), a progressive many‐lights algorithm for rendering complex indirect transport paths in, from, and to media. VBLs are efficient and can handle heterogeneous media, anisotropic scattering, and moderately glossy surfaces, while provably converging to ground truth. We inflate ray lights into beam lights with finite thicknesses to eliminate the remaining singularities. Furthermore, we devise several practical schemes for importance sampling the various transport contributions between camera rays, light rays, and surface points. VBLs produce artifact‐free images faster than VRLs, especially when glossy surfaces and/or anisotropic phase functions are present. Lastly, we employ a progressive thickness reduction scheme for VBLs in order to render results that converge to ground truth.     

Adaptive Cross‐sections of Anatomical Models

Medical illustrations have been used for a long time for teaching and communicating information for diagnosis or surgery planning. Illustrative visualization systems create methods and tools that adapt traditional illustration techniques to enhance the result of renderings. Clipping the volume is a popular operation in volume rendering for inspecting the inner parts, though it may remove some information of the context that is worth preserving. In this paper we present a new editing technique based on the use of clipping planes, direct structure extrusion, and illustrative methods, which preserves the context by adapting the extruded region to the structures of interest of the volumetric model. We will show that users may interactively modify the clipping plane and edit the structures to highlight, in order to easily create the desired result. Our approach works with segmented volume models and non‐segmented ones. In the last case, a local segmentation is performed on‐the‐fly. We will demonstrate the efficiency and utility of our method.     

A Java simulator of Rescorla and Wagner's prediction error model and configural cue extensions

In this paper we present the "R&W Simulator" (version 3.0), a Java simulator of Rescorla and Wagner's prediction error model of learning. It is able to run whole experimental designs, and compute and display the associative values of elemental and compound stimuli simultaneously, as well as use extra configural cues in generating compound values; it also permits change of the US parameters across phases. The simulator produces both numerical and graphical outputs, and includes a functionality to export the results to a data processor spreadsheet. It is user-friendly, and built with a graphical interface designed to allow neuroscience researchers to input the data in their own "language". It is a cross-platform simulator, so it does not require any special equipment, operative system or support program, and does not need installation. The "R&W Simulator" (version 3.0) is available free.     

Modelling and characterization of AlN-actuated microcantilevers vibrating in the first in-plane mode

The characterization of the first in-plane mode of aluminum nitride-actuated piezoelectric microcantilevers was carried out by using electrical and optical techniques. The top electrode of the cantilever was specifically designed to allow for an efficient electrical actuation of these in-plane modes. In order to confirm the in-plane nature of the modal vibration, the detection of the electrically induced movement was performed optically with the help of a stroboscopic microscope. In parallel, resonances were also measured electrically by means of an impedance analyzer. The quality factor and the resonant frequencies of the in-plane modes were estimated from the corresponding measurement data when applying both detection techniques. Our results show quality factor values as high as 3,000 for the first in-plane mode in air.     

Local search methods for efficient router nodes placement in wireless mesh networks

Wireless Mesh Networks (WMNs) are an important networking infrastructure for providing cost-efficient broadband wireless connectivity to a group of users. WMNs are increasingly being used in urban, metropolitan and municipal area networks for deployment of medical, transport, surveillance systems, etc. The performance and operability of WMNs largely depends on placement of mesh routers nodes in the geographical area to achieve network connectivity and stability. The objective is to find an optimal and robust topology of the mesh router network to support intelligent telecommunication services to clients such as adaptive and flexible wireless Internet access, mobile data, voice, video in addition to supporting other preferred client services. In this work, we propose and evaluate local search methods for intelligent placement of mesh routers in WMNs with a two fold objective: maximizing the size of the giant component in the network and user coverage. Given a grid area where to distribute a given number of mesh router nodes, which can have different radio coverage, and a number of fixed clients a priori distributed in the given area, local search methods explore different local movements and incrementally improve the quality of the router nodes placement in terms of network connectivity and user coverage. We have experimentally evaluated the proposed local search methods through a benchmark of generated instances of varying sizes. Moreover, different distributions of mesh clients (Uniform, Normal, Exponential and Weibull) are used. The experimental evaluation showed the good performance of local search methods for optimizing network connectivity and user coverage in WMNs.     

Multiobjective hierarchical control architecture for greenhouse crop growth

The problem of determining the trajectories to control greenhouse crop growth has traditionally been solved by using constrained optimization or applying artificial intelligence techniques. The economic profit has been used as the main criterion in most research on optimization to obtain adequate climatic control setpoints for the crop growth. This paper addresses the problem of greenhouse crop growth through a hierarchical control architecture governed by a high-level multiobjective optimization approach, where the solution to this problem is to find reference trajectories for diurnal and nocturnal temperatures (climate-related setpoints) and electrical conductivity (fertirrigation-related setpoints). The objectives are to maximize profit, fruit quality, and water-use efficiency, these being currently fostered by international rules. Illustrative results selected from those obtained in an industrial greenhouse during the last eight years are shown and described.