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ispartof: pages:229-237 ispartof: 2022 Sixth IEEE International Conference on Robotic Computing (IRC) pages:229-237 ispartof: 2022 Sixth IEEE International Conference on Robotic Computing (IRC) location:Italy date:5 Dec - 7 Dec 2022 status: published

We describe a novel method for video outpainting. The goal of outpainting is to fill in missing regions at the edges of video frames. Our focus lies on converting portrait (9:16) to landscape (16:9) video. In contrast, most video comple- tion research is focused on inpainting: filling a masked sec- tion within the frame based on the remaining, known pixels. Our proposed method consists of three main aspects: (1) We form a background estimation using video object seg- mentation and video inpainting methods, (2) we use optical flow to form temporal consistency, and (3) we propose im- age shifting to improve individual frame completions. Our method is able to successfully broaden the aspect ratio of a video. On most videos, we achieve realistic results. Only on videos with complex camera motion and foreground objects leaving the frame, the quality is less. In contrast to other state-of-the-art methods, our method is able to reconstruct the full frame, including unseen image parts. Moreover, it is temporally consistent. We evaluate our method on the DAVIS and YouTube-VOS datasets. The code is publicly available. ispartof: pages:687-695 ispartof: Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) pages:687-695 ispartof: IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) location:New Orleans, USA date:19 Jun - 24 Jun 2022 status: published

Over the recent years the role of mathematics in innovations for Circuits, Systems and Signal processing has increased considerably. The talk will overview the dynamical forces and their impact on the research and education. Examples will be given of mathematical methodologies for signal and image classification, data fusion, biomedical diagnostics with support vector machines, matrix and tensor decompositions. Also cryptographic algorithms are crucial in our modern society. Important lessons can be learned for research planning, dissemination and reproducibility as well as for teaching in engineering.

This paper presents the development of a multi campus, multidisciplinary curriculum for graduated engineers. Focus is placed on the societal role of engineering and the potential added value of technology for organisations in the social profit sector and for vulnerable groups in society that are the target public of these social profit organisations. The paper first demonstrates the role engineers have to play in the social sector by shortly presenting some best practice examples: an app that supports people with intellectual disabilities, a side table fitting the needs of elderly, a communication platform for people unable to read or write, etc.

© 2014 IEEE. While a wide range of disparity estimation algorithms exists, only few methods are available to analyze the quality of a disparity map. We present a new two-dimensional approach to disparity map evaluation using the stereo matching error and the temporal error. These measures give a good indication of stereo or multi-view performance on a 3D display. Results are illustrated on a ground truth disparity map with multiple distortions as well as on a commercially available disparity estimator using varying post-processing settings on a real stereoscopic video sequence. ispartof: 2014 International Conference on 3D Imaging, IC3D 2014 - Proceedings ispartof: International Conference on 3D Imaging (IC3D) location:BELGIUM, Liege date:9 Dec - 10 Dec 2014 status: published

Design-Technology co-optimization becomes a key knob to enable CMOS scaling. In this work we evaluate the technology options including lithography options as well as device options that are considered to enable N10 scaling by exploring their impact on representative designs such as standard cells, SRAM and analog contexts. This paper illustrates that the design angle needs to be considered early in the development of a technology node. This design assessment and decisions start from lithography constraints and options to power/performance, area and cost, all of which create the Design-Technology Co-Optimization space.

In this paper, we introduce a visualization tool for interactive and efficient exploration of high dimensional data using parallel coordinates. An algorithm is developed to find an optimal permutation of dimensions, which allows the data miner to immediately see the most important features or irregularities in the dataset. This is implemented as a genetic algorithm based on the travelling salesman problem using maximal correlation as fitness. Other features of the tool include selection operators to group the data such as selection by intersection or by angle, orthogonal and density plots complementing the parallel coordinates plot, manual arrangement of permutation order of the dimensions, possibility to show all plots necessary to see all dimensional relations and displaying a certain number of standard deviations for each dimension separately. The tool is applied to multiple gene prioritization cases in search of genes that are relevant to certain genetic disorders. The used datasets are obtained with the MerKator and Endeavour tools and include a Breast cancer, Cataract, Charcoth-Marie-Tooth and Cardiomyopathy dataset, as well as a dataset relating 29 diseases with 22206 genes. Our tool, manual and data can be downloaded from http://www.toomas.be/parcoord/.

It has been shown that kernel based regression (KBR) with a least squares loss has some undesirable properties from robustness point of view. KBR with more robust loss functions, e.g. Huber or Logistic losses, often give rise to more complicated computations. In classical statistics, robustness is improved by reweighting the original estimate. We study the influence of reweighting the LS-KBR estimate using three well-known weight functions and one new weight function called Myriad. Our results give practical guidelines in order to choose the weights, providing robustness and fast convergence. It turns out that Logistic and Myriad weights are suitable reweighting schemes when outliers are present in the data. In fact, the Myriad shows better performance over the others in the presence of extreme outliers (e.g. Cauchy distributed errors). These findings are then illustrated on toy example as well as on a real life data sets. Finally, we establish an empirical maxbias curve to demonstrate the ability of the proposed methodology.

Basic Circuits and Systems CAS education is crucial in the first phase of any electrical engineering curriculum, but increasingly under threat. This situation is in many ways similar to that of mathematics education in engineering. Creative shortcuts for teaching mathematics have recently been advocated in the “streetfighting mathematics approach”. Similar innovative, alternative ways can make the basic CAS education more effective. This special session aims to provide a forum where colleagues across the globe come together to share best practices, such as jewels or pedagogical shortcuts, and where they propose modern circuits, signals, and systems curricula for various target student audiences and discuss other related issues. Here we survey the contributions and discuss a case study, namely, the Thevenin/Helmholtz and Norton/Mayer equivalents.

We discuss certain aspects of the state of core education in circuits, signals, and systems and list a few current problems and issues. The colleagues who have contributed to the two special sessions on education not only share their valuable experiences and innovations, but also express their opinions on how to address a number of salient problems. In other subjects, such as mathematics, some educators have taken to drastic approaches—one so unusual that it was dubbed “street-fighting mathematics”. In a similar vein, we launch a debate on a collection of items for inclusion in, or exclusion from, basic circuits, signals, and systems education. We hope these ideas and novel practices will penetrate the diverse curricula around the globe.

The study of circuits and systems requires some basic reasoning with various equivalent interconnections of components like resistors, sources, ideal opamps, ideal transistors, short and open circuits…. Students should be able to handle a rich variety of such interconnections correctly and appropriately. Special components like nullators and norators bring in some valuable insights, flexibility and design methods based thereupon. From the practical experience of teaching nullators and norators in basic circuits courses for electrical engineering students, the authors stress a number of didactical goals and experiences. First, it is crucial that the students understand the notions of nullator and norator and are able to distinguish these from other components, such as short circuits, open circuits, resistors, and sources. Second, they should be able to reason correctly with interconnections that involve nullators and norators. Third, they should be able to find equivalents for circuits having nullators and norators. Analysis and design of circuits with nullators and norators will be presented. A particular case study of the use of nullators and norators for the implicit inversion of a 2 × 2 matrix will be used as an illustration of some unexpected results, which we will hardly find without nullators and norators. This will lead to an evaluation of the didactical processes of using nullators and norators.

Observability analysis is a very important tool in state estimation. For a given set of measurements and their geographical location in the system, it determines whether the state of the whole system can be estimated. In this paper a numerical observability analysis, applicable to distribution systems is discussed and applied to the IEEE 34 bus test feeder. The method is based on the inverse function theory and the Jacobian matrix of the system. By calculating the dependent columns of the Jacobian matrix it is possible to determine the unobservable branches in the system. This also gives an indication of how many linearly independent pseudo-measurements are required to make the distribution system observable. Because the R=X ratio is not negligible in the distribution lines, a transformation has been used to simplify the observability analysis.

The mathematics of circuits and systems requires some basic knowledge of linear algebra, differential equations, and transforms. Moreover many concepts and methods of basic circuits and systems courses can and should rely on sharp mathematical insight. Efficient and effective teaching of the basic mathematics and the basic circuits and systems courses for electrical engineering students can hence benefit from a strong link between the two. The paper gives an inventory of the relevant subjects and describes the different ways that such subjects can be taught and linked with circuits and systems Experience with this approach and interesting modules and references are presented.

It is the aim of this paper to discuss the various critical elements in the education of the mathematics of circuits and systems in the present context of a lean, efficient, and performant, but above all attractive electrical engineering education. The paper motivates the need for a solid mathematical basis, and strong concepts, that are more than shallow recipes, for conceptually interested students, at an early phase of the bachelor education. Such courses should be taught by motivated teachers in an attractive, motivational way.

This paper addresses what the influence of uncertainty on ferromagnetic material properties is on the torque yielded by ferromagnetic cylinders rotating at high speeds. To that end, two state-of-the-art high-order stochastic solution approaches, the stochastic collocation and the stochastic Galerkin method, are applied to a nonlinear convection-diffusion problem with random coefficients and their performance is compared. © 2011 IEEE. ispartof: IEEE Transactions on Magnetics vol:47 issue:5 pages:1182-1185 ispartof: location:Chicago, Illinois, USA status: published

It is generally understood that interpreting depth from monoscopic images inherently induces the problem of object segmentation and context recognition. A common way to deal with this complexity is to focus on one aspect (e.g. segmentation) and largely constrain or skip the other (e.g. scene classification). In our approach, we practically reconcile the two paths. We start by defining several depth profiles, providing rough estimates for both background and foreground, while reflecting common photographic and cinematic practices and rules. The idea is to assign one or more of these profiles to an image - based on the output of multiple classifiers, and apply an image-adaptive bilateral filter to align the depth with object edges. From extensive trials, we conclude that robust classification and visual performance can be achieved with this approach on a variety of content. ©2009 IEEE. ispartof: pages:2365-2368 ispartof: Proceedings - International Conference on Image Processing, ICIP pages:2365-2368 ispartof: 16th IEEE International Conference on Image Processing location:EGYPT, Cairo date:7 Nov - 10 Nov 2009 status: published

We propose an interface for creating a depth map for a 2D picture. The image and depth map can be used for 3D display on an auto-stereoscopic photo frame. Our new interface does not require the user to draw on the picture or point at an object in the picture. Instead, semantic questions are asked about a given indicated position in the picture. This semantic information is then translated automatically into a depth map. ©2009 IEEE. ispartof: pages:13-+ ispartof: 3DTV-CON 2009 - 3rd 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video, Proceedings pages:13-+ ispartof: 3DTV Conference - True Vision - Capture, Transmission and Display of 3D Video location:GERMANY, Potsdam date:4 May - 6 May 2009 status: published

International audience; A new way to interact with small devices consists in embedding tiny Web servers, allowing the devices to serve fully-fledged Web applications. When the device needs to keep its users up-to-date of its internal state, the Web application has to use an event publication solution. Several works have recently been conducted in order to evaluate the trade-offs of various Web-based event notification solutions. In this paper, we propose to evaluate the feasibility of event notification in embedded Web applications. We conduct a large set of experiments in order to compare various push and pull based approaches for embedded systems. We show that a push-based approach can be very efficient in most situations, both in terms of client consistency and of scalability.

This paper deals with the Riemannian geometry of the set of symmetric positive semidefinite matrices of fixed rank. This set is studied as an embedded submanifold of the real matrices equipped with the usual Euclidean metric. With this structure, we derive expressions of the tangent space and geodesics of the manifold, suitable for efficient numerical computations.

This paper discusses a number of critical issues that occur in the teaching process of basic circuit and systems concepts and methods to electrical engineering students. Different role models are introduced and some views on alternative choices are made. It is felt that extensive discussion and debate is desirable in order to enhance the efficacy of the teaching, its impact in the electrical engineering education and in order to increase the intrinsic interest of the students.

Super-resolution algorithms combine multiple low resolution images into a single high resolution image. They have received a lot of attention recently in various application domains such as HDTV, satellite imaging, and video surveillance. These techniques take advantage of the aliasing present in the input images to reconstruct high frequency information of the resulting image. One of the major challenges in such algorithms is a good alignment of the input images: subpixel precision is required to enable accurate reconstruction. In this paper, we give an overview of some subspace techniques that address this problem. We first formulate super-resolution in a multichannel sampling framework with unknown offsets. Then, we present three registration methods: one approach using ideas from variable projections, one using a Fourier description of the aliased signals, and one using a spline description of the sampling kernel. The performance of the algorithms is evaluated in numerical simulations. © 2008 IEEE. ispartof: pages:645-648 ispartof: Proceedings - International Conference on Image Processing, ICIP pages:645-648 ispartof: 15th IEEE International Conference on Image Processing (ICIP 2008) location:CA, San Diego date:12 Oct - 15 Oct 2008 status: published

How often have you been able to implement an algorithm as it is described in a paper? And when you did, were you confident that you had exactly the same parameter values and results as the authors of the paper? All too often, articles do not describe all the details of an algorithm and thus prohibit an implementation by someone else. In this paper, we describe our experience with reproducible research, a paradigm to allow other people to reproduce with minimal effort the results we have obtained. We discuss both the reproducibility of data and algorithms, and give examples for each of them. The effort required to make research reproducible is compensated by a higher visibility and impact of the results. © 2007 IEEE. ispartof: pages:1253-1256 ispartof: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings vol:4 pages:1253-1256 ispartof: 32nd IEEE International Conference on Acoustics, Speech and Signal Processing location:HI, Honolulu date:15 Apr - 20 Apr 2007 status: published

It is the aim of reproducible research to provide mechanisms for objective comparison of methods, algorithms, software and procedures in various research topics. In this paper, we discuss the role of data sets, benchmarks and competitions in the fields of system identification, time series prediction, classification, and pattern recognition in view of creating an environment of reproducible research. Important elements are the data sets, their origin, and the comparison measures that will be used to rank the performance of the methods. The issues are discussed, a comparison is made and recommendations are given.

In this paper Josephson junctions are used in order to generate n-scroll and n-scroll hypercube attractors. We propose to use of the Josephson junction in a general Jerk circuit in such a way that there is no need for synthesizing the nonlinearity towards n-scroll and n-scroll hypercube attractors. The results are illustrated with computer simulations.

A software tool with the aim of learning new CNN templates and incorporating the ability to tune templates to individual chip instances is presented. During demonstration, the training process of the grayscale constrained trigger-wave template [1] will be shown. The audience can test the tool by proposing their own operation to be learned/tuned.

In this demonstration we will present an application of a fast and robust face tracking algorithm implemented with a CNN Universal Machine chip. The application is the driving of a wheelchair according to predefined movements of the user's head. A 3D model of a wheelchair is used in order to demonstrate the driving mechanism.

An algorithm for fast and robust face tracking with the CNN Universal Machine is proposed in this paper. It is applied to a driving mechanism for a wheelchair with an on-chip implementation. A novel object tracking CNN visual algorithm is introduced and employed in the tracking of multiple face features. The speed and robustness of this method are achieved due to the parallelism in the visual algorithm, and the tracking of multiple face features. The tracking algorithm is designed to achieve a high frame rate and exploit the specific properties of face features. The face tracking method proposed here was implemented on a Bi-I stand alone cellular vision system and applied to a wheelchair driving mechanism. The template operations were trained and/or fine-tuned in order to generate chip-specific robust templates. In order to improve performanee in environments with varying illumination, an adaptive image capture procedure was also introduced. Our simulations with a 3D model wheelchair showed that the final algorithm is capable of performing tracking with a frame rate of 92 frames/sec, which is supposedly enough for real-time driving in most of the real life situations.

Aliasing artifacts in images are visually very disturbing. Therefore, most imaging devices apply a low-pass filter before sampling. This removes all aliasing from the image, but it also creates a blurred image. Actually, all the image information above half the sampling frequency is removed. In this paper, we present a new method for the reconstruction of a high resolution image from a set of highly under-sampled and thus aliased images. We use the information in the entire frequency spectrum, including the aliased part, to create a sharp, high resolution image. The unknown relative shifts between the images are computed using a subspace projection approach. We show that the projection can be decomposed into multiple projections onto smaller subspaces. This allows for a considerable reduction of the overall computational complexity of the algorithm. A high resolution image can then be reconstructed from the registered low resolution images. Simulation results show the validity of our algorithm. © 2005 IEEE. ispartof: pages:889-892 ispartof: Proceedings - International Conference on Image Processing, ICIP vol:1 pages:889-892 ispartof: IEEE International Conference on Image Processing (ICIP 2005) location:ITALY, Genoa date:11 Sep - 14 Sep 2005 status: published

The concept of collision free hash functions has been shown to be a useful building block of signature schemes and message authentication schemes. In this paper, a fast and secure proposal is made for a 2n-bit collison free hash function based on an n-bit encryp tion algorithm. In case of the DES, the length of the result is 128 bits, which suffices to thwart a birthday attack.

Using the properties of universal approximation of multilayer perceptron neural networks, a class of discrete nonlinear dynamical systems are modeled by a perceptron with two hidden layers. The authors' backpropagation algorithm is then used to train the model to identify the nonlinear systems to a desired degree of accuracy. Based on the identified model, a one step ahead predictive control scheme is proposed in which the future control inputs are obtained through some nonlinear optimization process. Making use of the online learning properties of neural networks, the predictive control scheme is further developed into an adaptive one which is robust to the incompleteness of identification. Simulation results show that the control scheme works well even for some very complicated nonlinear systems.

This paper presents an adaptive on-line technique for the real-time extraction of the antepartum Fetal Electrocardiogram (FECG) from cutaneous recordings. The method combines a number of cutaneously recorded potential signals in order to eliminate the omnipresent strong maternal ECG (MECG) and to detect an optimal FECG. The algorithm for this signal separation is based on the Singular Value Decomposition (SVD) of the data matrix. Crucial for the success of the method is an appropriate electrode placement strategy. At the moment a realtime PC-based unit for bed-side monitoring of the antepartum FECG is under development.

We present a recursive nonlinear identification technique based on feedforward neural networks. A distinct feature of the proposed technique is the use of radial-basis-function (RBF) neural nets as generic discrete nonlinear model structure. RBF nets have enabled us to devise a stable weight updating algorithm that guarantees the convergence of the weights to the target values. A simulation example is provided to illustrate the effectiveness of the method.

Due to security requirements, services and management of Integrated Broadband Communication (IBC) are crucially dependent on the use of cryptographic techniques. Within the RACE program (Research and Development in Advanced Communications Technologies in Europe), the RIPE project (RACE Integrity Primitives Evaluation) aims to put forward a portfolio of such techniques to meet the anticipated security requirements of IBC. The goal of this contribution is to describe background and status of the RIPE project.

The numerical solution of a parabolic partial differential equation is usually calculated by a time stepping method. This precludes the efficient use of vectorization and parallelism, if the problem to be solved on each time level is not very large. In this paper we present an algorithm which overcomes the limitations of the standard marching schemes by solving for the solution on all the time levels simultaneously. The method is applicable to linear and nonlinear problems on arbitrary domains. It can be used to solve initial-boundary value problems as well as time-periodic equations.

Often, in engineering education there is much emphasis on theoretical issues, especially during the first years. Still, students should be exposed to more than just theoretical knowledge. This paper describes a project-oriented approach to undergraduate teaching in the field of electrical power engineering applied in the Department of Electrical Engineering of the K.U.Leuven University, Belgium. Two projects offered to undergraduate students of the second year are presented. The first project lets the students make their own small green power plant. The second project deals with the prediction of electricity consumption in a liberalized energy market.

Pattern formation occurring on the ACE (analogic cellular engine)16k CNN (cellular neural network) chip is presented. The CNN chip can be programmed with a cloning template in order to generate spiral waves and autowaves. The waves diffract from the internal sources which cannot be relocated on the network. However, by using initial and/or input images, sources (external sources) can be located at any place on the network. Furthermore a competition between autowaves generated by external and internal sources is observed. Propagation of autowaves on the inhomogeneous CNN array, formed by the fixed-state map, is presented.

Kernel based methods suffer from exceeding time and memory requirements when applied on large datasets since the involved optimization problems typically scale polynomially in the number of data samples. As a remedy we propose both working on a reduced set (for fast evaluation) and at the same time keeping the number of model parameters small (for fast training). Departing from the Nystrom based feature approximation we describe fixed-size least squares support vector machine in the context of primal space least squares regression, to extend it with a supervised counterpart, sparse kernel partial least squares. The model is illustrated on a large scale example.

In this paper, a novel true random bit generator (TRBG) based on a double scroll attractor is proposed. The double scroll attractor is obtained from a simple model which is qualitatively similar to Chua's Circuit. In order to face the challenge of using the proposed TRBG in cryptography, the proposed TRBG is subjected to statistical tests which are the well-known FIPS-140-1 and Diehard test suites in the area of cryptography. The proposed TRBG successfully passes all these tests and can be implemented in integrated circuits.