In this paper, we address the problem of non-parametric template matching which does not assume any specific deformation models. In real-world matching scenarios, deformation between a template and a matching result usually appears to be non-rigid and non-linear. We propose a novel approach called local rigidity constraints (LRC). LRC is built based on an assumption that the local rigidity, which is referred to as structural persistence between image patches, can help the algorithm to achieve better performance. A spatial relation test is proposed to weight the rigidity between two image patches. When estimating visual similarity under an unconstrained environment, high-level similarity (e.g. with complex geometry transformations) can then be estimated by investigating the number of LRC. In the searching step, exhaustive matching is possible because of the simplicity of the algorithm. Global maximum is given out as the final matching result. To evaluate our method, we carry out a comprehensive comparison on a publicly available benchmark and show that our method can outperform the state-of-the-art method.

In this paper, we address the problem of projective template matching which aims to estimate parameters of projective transformation. Although homography can be estimated by combining key-point-based local features and RANSAC, it can hardly be solved with feature-less images or high outlier rate images. Estimating the projective transformation remains a difficult problem due to high-dimensionality and strong non-convexity. Our approach is to quantize the parameters of projective transformation with binary finite field and search for an appropriate solution as the final result over the discrete sampling set. The benefit is that we can avoid searching among a huge amount of potential candidates. Furthermore, in order to approximate the global optimum more efficiently, we develop a level-wise adaptive sampling (LAS) method under genetic algorithm framework. With LAS, the individuals are uniformly selected from each fitness level and the elite solution finally converges to the global optimum. In the experiment, we compare our method against the popular projective solution and systematically analyse our method. The result shows that our method can provide convincing performance and holds wider application scope.

With the appearance of large OLED panels, the OLED TV industry has experienced significant growth. However, this technology is still in the early stages of commercialization, and some technical challenges remain to be overcome. During the development phase of a product, power consumption is one of the most important considerations. To reduce power consumption in OLED displays, we propose a method based on just-noticeable difference (JND). JND refers to the minimum visibility threshold when visual content is altered and results from physiological and psychophysical phenomena in the human visual system (HVS). A JND model suitable for OLED displays is derived from numerous experiments with OLED displays. With the use of JND, it is possible to reduce power consumption while minimizing perceptual image quality degradation.

In this paper, the integration of dynamic plant-wide optimization and distributed generalized predictive control (DGPC) is presented for serially connected processes. On the top layer, chance-constrained programming (CCP) is employed in the plant-wide optimization with economic and model uncertainties, in which the constraints containing stochastic parameters are guaranteed to be satisfied at a high level of probability. The deterministic equivalents are derived for linear and nonlinear individual chance constraints, and an algorithm is developed to search for the solution to the joint probability constrained problem. On the lower layer, the distributed GPC method based on neighborhood optimization with one-step delay communication is developed for on-line control of the whole system. Simulation studies for furnace temperature set-points optimization problem of the walking-beam-type reheating furnace are illustrated to verify the effectiveness and practicality of the proposed scheme.

Recently in an SDN/NFV-enabled network, a consolidated middlebox is proposed in which middlebox functions required by a network flow are provided at a single machine in a virtualized manner. With the promising advantages such as simplifying network traffic routing and saving resources of switches and machines, consolidated middleboxes are going to replace traditional middleboxes in the near future. However, the location of consolidated middleboxes may affect the performance of an SDN/NFV network significantly. Accordingly, the consolidated middlebox positioning problem in an SDN/NFV-enabled network must be addressed adequately with service chain constraints (a flow must visit a specific type of consolidated middlebox), resource constraints (switch memory and processing power of the machine), and performance requirements (end-to-end delay and bandwidth consumption). In this paper, we propose a novel solution of the consolidated middlebox positioning problem in an SDN/NFV-enabled network based on flow clustering to improve the performance of service chain flows and utilization of a consolidated middlebox. Via extensive simulations, we show that our solution significantly reduces the number of routing rules per switch, the end-to-end delay and bandwidth consumption of service flows while meeting service chain and resource constraints.

As the demand for higher transmission rates and spectral efficiency is steadily increasing, the research and development of novel mobile communication systems has gained momentum. This paper focuses on providing a comprehensive survey of research and development activities on fifth generation mobile communication systems in Japan. We try to survey a vast area of wireless communication systems and the developments that led to future 5G systems.

This paper describes a numerical assessment methodology of pacemaker EMI triggered by HF-band wireless power transfer system. By using three dimensional full-wave numerical simulation based on finite element method, interference voltage induced at the connector of the pacemaker inside the phantom that is used for in-vitro EMI assessment is obtained. Simulated example includes different exposure scenarios in order to estimate the maximum interference voltage.

A novel computational method based on a combination of the method of moments in the complex frequency domain and the fast inverse Laplace transform is proposed for solving time-domain electromagnetic problems. Using our proposed method, it is easy to estimate and control the computational error, and the observation time can be selected independently. We investigate canonical scattering problems and verify these advantages.

The 60 GHz band compact-range communication is very promising for short-time, short distance communication. Unfortunately, due to the short wavelengths in this frequency band the shadowing effects caused by human bodies, furniture, etc are severe and need to be modeled properly. The numerical methods like the finite-difference time-domain method (FDTD), the finite-element method (FEM), the method of moments (MoM) are unable to compute the field scattered by large objects due to their excessive time and memory requirements. Ray-based approaches like the geometrical theory of diffraction (GTD), uniform geometrical theory of diffraction (UTD), uniform asymptotic theory of diffraction (UAT) are effective and popular solutions but suffer from computation of corner-diffracted field, field at the caustics. Fresnel zone number (FZN) adopted modified edge representation (MER) equivalent edge current (EEC) is an accurate and fast high frequency diffraction technique which expresses the fields in terms of line integration. It adopts distances, rather than the angles used in GTD, UTD or UAT but still provides uniform and highly accurate fields everywhere including geometrical boundaries. Previous work verified this method for planar scatterers. In this work, FZN MER EEC is used to compute field distribution in the millimeter-wave compact range communication in the presence of three dimensional scatterers, where shadowing effects rather than multi-path dominate the radio environments. First, circular cylinder is disintegrated into rectangular plate and circular disks and then FZN MER is applied along with geodesic path loss. The dipole wave scattering from perfectly conducting circular cylinder is discussed as numerical examples.

Mass-market head mounted displays (HMDs) are currently attracting a wide interest from consumers because they allow immersive virtual reality (VR) experiences at an affordable cost. Flying over a virtual environment is a common application of HMD. However, conventional keyboard- or mouse-based interfaces decrease the level of immersion. From this motivation, we design three types of immersive gesture interfaces (bird, superman, and hand) for the flyover navigation. A Kinect depth camera is used to recognize each gesture by extracting and analyzing user's body skeletons. We evaluate the usability of each interface through a user study. As a result, we analyze the advantages and disadvantages of each interface, and demonstrate that our gesture interfaces are preferable for obtaining a high level of immersion and fun in an HMD based VR environment.

We present a design method for miniaturizing double stub resonators that are potentially very useful for wide range of applications but have limited usage for MMICs due to their large footprint. The analytical design model, which we introduce in this paper, allows for determining the capacitances needed to achieve the targeted shrinking ratio while maintaining the original loaded-Q before miniaturization. To verify the model, 18-GHz stub resonators that are around 40% of the original sizes were designed and fabricated in GaAs MMIC technology. The effectiveness of the proposed technique is also demonstrated by a 9-GHz low phase-noise oscillator using the miniaturized resonator.

Recently, due to the development of design and manufacturing technologies for VLSI systems, an embedded system becomes more and more complex. Consequently, not only the performance of chips, but also the flexibility and dynamic adaptation of the implemented systems are required. To achieve these requirements, a partially reconfigurable device is promising. In this paper, we propose an efficient data structure to manage the reconfigurable units. And then, on the assumption that each task utilizes the rectangle shaped resources, a very simple MER enumeration algorithm based on this data structure is proposed. By utilizing the result of MER enumeration, the free space on the reconfigurable device can be used sufficiently. We analyze the complexity of the proposed algorithm and confirm its efficiency by experiments.

Two plasmonic band-bass filters are analyzed: one is a grating-type filter and the other is a slit-type filter. The former shows a band-pass characteristic with a high transmission for a two-dimensional structure, while the latter exhibits a high transmission even for a three-dimensional structure with a thin metal layer.

In this paper we propose a novel classification method for the multiple k-nearest neighbor (MkNN) classifier and show its practical application to medical image processing. The proposed method performs fine classification when a pair of the spatial coordinate of the observation data in the observation space and its corresponding feature vector in the feature space is provided. The proposed MkNN classifier uses the continuity of the distribution of features of the same class not only in the feature space but also in the observation space. In order to validate the performance of the present method, it is applied to the tissue characterization problem of coronary plaque. The quantitative and qualitative validity of the proposed MkNN classifier have been confirmed by actual experiments.

Recently, high-level synthesis techniques for FPGA designs (FPGA-HLS techniques) are strongly required in various applications. Both interconnection delays and clock skews have a large impact on circuit performance implemented onto FPGA, which indicates the need for floorplan-driven FPGA-HLS algorithms considering them. To appropriately estimate interconnection delays and clock skews at HLS phase, a reasonable model to estimate them becomes essential. In this paper, we demonstrate several experiments to characterize interconnection delays and clock skews in FPGA and propose novel estimate models called “IDEF” and “CSEF”. In order to evaluate our models, we integrate them into a conventional floorplan-driven FPGA-HLS algorithm. Experimental results demonstrate that our algorithm can realize FPGA designs which reduce the latency by up to 22% compared with conventional approaches.

A fully synthesizable all-digital phase-locked loop (AD-PLL) with a stochastic time-to-digital converter (STDC) is proposed in this paper. The whole AD-PLL circuit design is based on only standard cells from digital library, thus the layout of this AD-PLL can be automatically synthesized by a commercial place-and-route (P&R) tool with a foundry-provided standard-cell library. No manual layout and process modification is required in the whole AD-PLL design. In order to solve the delay mismatch issue in the delay-line-based time-to-digital converter (TDC), an STDC employing only standard D flip-flop (DFF) is presented to mitigate the sensitivity to layout mismatch resulted from automatic P&R. For the stochastic TDC, the key idea is to utilize the layout uncertainty due to automatic P&R which follows Gaussian distribution according to statistics theory. Moreover, the fully synthesized STDC can achieve a finer resolution compared to the conventional TDC. Implemented in a 28nm fully depleted silicon on insulator (FDSOI) technology, the fully synthesized PLL consumes only 480µW under 1.0V power supply while operating at 0.9GHz. It achieves a figure of merit (FoM) of -231.1dB with 4.0ps RMS jitter while occupying 0.0055mm2 chip area only.

In this letter, a micro-expression recognition method is investigated by integrating both spatio-temporal facial features and a regression model. To this end, we first perform a multi-scale facial region division for each facial image and then extract a set of local binary patterns on three orthogonal planes (LBP-TOP) features corresponding to divided facial regions of the micro-expression videos. Furthermore, we use GSLSR model to build the linear regression relationship between the LBP-TOP facial feature vectors and the micro expressions label vectors. Finally, the learned GSLSR model is applied to the prediction of the micro-expression categories for each test micro-expression video. Experiments are conducted on both CASME II and SMIC micro-expression databases to evaluate the performance of the proposed method, and the results demonstrate that the proposed method is better than the baseline micro-expression recognition method.

Today, computer vision is used in different applications for intelligent transportation systems like: traffic surveillance, driver assistance, law enforcement etc. Amongst these applications, we are concentrating on speed measurement for law enforcement. In law enforcement applications, the presence of the license plate in the scene is a presupposition and metric parameters like vehicle's speed are to be estimated with a high degree of precision. The novelty of this paper is to propose a new precise, practical and fast procedure, with hierarchical architecture, to estimate the homraphic transform of the license plate and using this transform to estimate the vehicle's speed. The proposed method uses the RANSAC algorithm to improve the robustness of the estimation. Hence, it is possible to replace the peripheral equipment with vision based systems, or in conjunction with these peripherals, it is possible to improve the accuracy and reliability of the system. Results of experiments on different datasets, with different specifications, show that the proposed method can be used in law enforcement applications to measure the vehicle's speed.

We describe a calculation tool and modeling methods to find self and mutual inductance and current distribution in superconductive multilayer circuit layouts. Accuracy of the numerical solver is discussed and compared with experimental measurements. Effects of modeling parameter selection on calculation results are shown, and we make conclusions on the selection of modeling parameters for fast but sufficiently accurate calculations when calibration methods are used. Circuit theory for the calculation of branch impedances from the output of the numerical solver is discussed, and compensation for solution difficulties is shown through example. We elaborate on the construction of extraction models for superconductive integrated circuits, with and without resistive branches. We also propose a method to calculate current distribution in a multilayer circuit with multiple bias current feed points. Finally, detailed examples are shown where the effects of stacked vias, bias pillars, coupling, ground connection stacks and ground return currents in circuit layouts for the AIST advanced process (ADP2) and standard process (STP2) are analyzed. We show that multilayer inductance and current distribution extraction in such circuits provides much more information than merely branch inductance, and can be used to improve layouts; for example through reduced coupling between conductors.

Laplacian operator is a basic tool for image processing. For an image with regular pixels, the Laplacian operator can be represented as a stencil in which constant weights are arranged spatially to indicate which picture cells they apply to. However, in a discrete spherical image the image pixels are irregular; thus, a stencil with constant weights is not suitable. In this paper a spherical Laplacian operator is derived from Gauss's theorem; which is suitable to images with irregular pixels. The effectiveness of the proposed discrete spherical Laplacian operator is shown by the experimental results.