Light-weight salient foreground detection for embedded smart cameras

An embedded smart camera is a stand-alone unit that not only captures images, but also includes a processor, memory and communication interface. Battery-powered, embedded smart cameras introduce many additional challenges since they have very limited resources, such as energy, processing power and memory. Computer vision algorithms running on these camera boards should be light-weight and efficient. Considering the memory requirements of an algorithm and its portability to an embedded processor should be an integral part of the algorithm design in addition to the accuracy requirements. This paper presents a light-weight and efficient background modeling and foreground detection algorithm that is highly robust against lighting variations and non-static backgrounds including scenes with swaying trees, water fountains and rain. Compared to many traditional methods, the memory requirement for the data saved for each pixel is very small in the proposed algorithm. Moreover, the number of memory accesses and instructions are adaptive, and are decreased depending on the amount of activity in the scene. Each pixel is treated differently based on its history, and instead of requiring the same number of memory accesses and instructions for every pixel, we require less instructions for stable background pixels. The plot of the number of unstable pixels at each frame also serves as a tool to find the video portions with high activity. The proposed method selectively updates the background model with an automatically adaptive rate, thus can adapt to rapid changes. As opposed to traditional methods, pixels are not always treated individually, and information about neighbors is incorporated into decision making. The results obtained with nine challenging outdoor and indoor sequences are presented, and compared with the results of different state-of-the-art background subtraction methods. The ROC curves and memory comparison of different background subtraction methods are also provided. The experimental results demonstrate the success of the proposed light-weight salient foreground detection method.     

Illustrating volume data sets and layered models with importance-aware composition

Non-photorealistic (illustrative) rendering augments typical rendering models to selectively emphasize or de-emphasize specific structures of rendered objects. Illustrative techniques may affect not only the rendering style of specific portions of an object but also their visibility, ensuring that less important regions do not occlude more important ones. Cutaway views completely remove occluding, unimportant structures—possibly also removing valuable context information—while existing solutions for smooth reduction of occlusion based on importance lack precise visibility control, simplicity and generality. We introduce a new front-to-back fragment composition equation that directly takes into account a measure of sample importance and allows smooth and precise importance-based visibility control. We demonstrate the generality of our composition equation with several illustrative effects, which were obtained by using a set of importance measures calculated on the fly or defined by the user. The presented composition method is suitable for direct volume rendering as well as rendering of layered 3D models. We discuss both cases and show examples, though focusing mainly on illustration of volumetric data.     

Development of an Autonomous Robot for Gas Storage Spheres Inspection

Inspection for corrosion of gas storage spheres at the welding seam lines must be done periodically. Until now this inspection is being done manually and has a high cost associated to it and a high risk of inspection personel injuries. The Brazilian Petroleum Company, Petrobras, is seeking cost reduction and personel safety by the use of autonomous robot technology. This paper presents the development of a robot capable of autonomously follow a welding line and transporting corrosion measurement sensors. The robot uses a pair of sensors each composed of a laser source and a video camera that allows the estimation of the center of the welding line. The mechanical robot uses four magnetic wheels to adhere to the sphere’s surface and was constructed in a way that always three wheels are in contact with the sphere’s metallic surface which guarantees enough magnetic atraction to hold the robot in the sphere’s surface all the time. Additionally, an independently actuated table for attaching the corrosion inspection sensors was included for small position corrections. Tests were conducted at the laboratory and in a real sphere showing the validity of the proposed approach and implementation.     

Electrical resistivity in ferromagnetic NiCu alloys near the Curie point

Direct measurements of the temperature derivative of the electrical resistivity d/dT have been made on several ferromagnetic NiCu alloys with high Cu content (20, 30, 40, 50.4 at %). For Ni₈₀Cu₂₀ and Ni₇₀Cu₃₀ the results closely resemble the general pattern found in pure ferromagnets: d/dT - b – a ln ¦¦, for 10^–3 ¦¦ 10^–1, with a and b constants and = (T/T _c )– 1. In Ni₆₀Cu₄₀ the rounding off of the magnetic transition is already so pronounced that a similar analysis is hardly significant. In the Ni_49.6Cu_50.4 sample negative values of d/dT were confirmed above ~165 K. The possible theoretical implications of the results are briefly discussed.Work supported by Instituto de Alta Cultura, Portugal (Project PF1).     

Modelling and optimization of laminated adaptive shells of revolution

In this paper two shell finite element models are presented for the structural analysis of composite laminated piezoelectric shells. One is an axisymmetric conical frustum with two nodal rings and the other is a conic shell panel with eight nodes. Both models are based in a mixed laminated theory that combines a higher order shear deformation theory for the mechanical displacement field with a layerwise representation with linear functions for the electric potential through each piezoelectric layer. In order to obtain the optimal design sensitivities analysis and optimization techniques based in the nonlinear mathematical programming are used. The design objectives can be the minimization of the deformed structure or the maximization of the natural fundamental frequency and the design variables are the electric potential difference applied to the actuators or the ply thicknesses among others.     

Mining sequential patterns by pattern-growth: the PrefixSpan approach

Sequential pattern mining is an important data mining problem with broad applications. However, it is also a difficult problem since the mining may have to generate or examine a combinatorially explosive number of intermediate subsequences. Most of the previously developed sequential pattern mining methods, such as GSP, explore a candidate generation-and-test approach [R. Agrawal et al. (1994)] to reduce the number of candidates to be examined. However, this approach may not be efficient in mining large sequence databases having numerous patterns and/or long patterns. In this paper, we propose a projection-based, sequential pattern-growth approach for efficient mining of sequential patterns. In this approach, a sequence database is recursively projected into a set of smaller projected databases, and sequential patterns are grown in each projected database by exploring only locally frequent fragments. Based on an initial study of the pattern growth-based sequential pattern mining, FreeSpan [J. Han et al. (2000)], we propose a more efficient method, called PSP, which offers ordered growth and reduced projected databases. To further improve the performance, a pseudoprojection technique is developed in PrefixSpan. A comprehensive performance study shows that PrefixSpan, in most cases, outperforms the a priori-based algorithm GSP, FreeSpan, and SPADE [M. Zaki, (2001)] (a sequential pattern mining algorithm that adopts vertical data format), and PrefixSpan integrated with pseudoprojection is the fastest among all the tested algorithms. Furthermore, this mining methodology can be extended to mining sequential patterns with user-specified constraints. The high promise of the pattern-growth approach may lead to its further extension toward efficient mining of other kinds of frequent patterns, such as frequent substructures.     

Analyzing Architectural Evolution Issues of Multimedia Frameworks

The growing complexity in the development of Web-based services in general, and multimedia services in particular, makes necessary the application of sound development methods. New multimedia devices, coding algorithms, network protocols, etc., are continually appearing but, unfortunately, current solutions for developing multimedia applications do not accurately support architectural evolution issues for already deployed applications. Thus, the latest Software Engineering technologies should be applied to the development of open, reusable, and high-quality multimedia and Web-based software. In this paper, we apply component and framework technologies, two of the current trends in Software Engineering, to the development of multimedia services over the Web, presenting and comparing widespread solutions in use today.     

The transaction costs theory in international business research: a bibliometric study over three decades

Transaction costs theory (TCT) has long been an important conceptual lens for examining International Business (IB) phenomena and perhaps especially relevant for the study of multinational corporations, entry mode choices and location selection. In this paper we examine the extent to which TCT been used and has impacted IB research. Methodologically, we conduct a bibliometric study of the articles published on nine top journals for publishing IB-related research. We use Jean-François Hennart’s research as the key marker for TCT in IB research given that Hennart’s work has been a hallmark in the discipline. On a sample of 377 articles published between 1982 and 2010, and using the works rather than the authors as the unit of analysis, we analyze citations, co-citations and a spatial visualization of the intellectual research themes delved into. Our analyses provide insights on the influence of Hennart but more broadly of TCT on IB research over the past three decades. We conclude that the TCT has a pervasive influence on a large array of IB research and that Hennart’s work is boundary-spanning, connecting several research themes.     

Simulation of membrane chemical degradation in a proton exchange membrane fuel cell by computational fluid dynamics

Membrane chemical degradation is a major contributor to the still limited lifetime of proton exchange membrane (PEM) fuel cells. In the present work, this phenomenon is simulated by computational fluid dynamics (CFD). The main advantage of the CFD model is that it can provide the degradation profile across the cell active area. Results reveal that degradation accelerates when voltage, temperature and pressure are increased and when reactants humidity and membrane thickness are decreased. Moreover, membrane deterioration is found to be more severe where oxygen pressure is higher, and more heterogeneous when oxygen distribution is less uniform. Generally, conditions that increase current production and thus oxygen depletion along the cell increase degradation heterogeneity. The flow field design is also found to influence the membrane degradation spatial profile. The modeling strategy here applied, the incorporation of a degradation sub-model into a general-purpose CFD code, can be used to include other degradation mechanisms.