In this paper, a novel approach is proposed for stereo vision-based ground plane detection at superpixel-level, which is implemented by employing a Disparity Texture Map in a convolution neural network architecture. In particular, the Disparity Texture Map is calculated with a new Local Disparity Texture Descriptor (LDTD). The experimental results demonstrate our superior performance in KITTI dataset.

Structure tensor analysis on epipolar plane images (EPIs) is a successful approach to estimate disparity from a light field, i.e. a dense set of multi-view images. However, the disparity range allowable for the light field is limited because the estimation becomes less accurate as the range of disparities become larger. To overcome this limitation, we developed a new method called sheared EPI analysis, where EPIs are sheared before the structure tensor analysis. The results of analysis obtained with different shear values are integrated into a final disparity map through a smoothing process, which is the key idea of our method. In this paper, we closely investigate the performance of sheared EPI analysis and demonstrate the effectiveness of the smoothing process by extensively evaluating the proposed method with 15 datasets that have large disparity ranges.

Effective indoor localization is the essential part of VR (Virtual Reality) and AR (Augmented Reality) technologies. Tracking the RGB-D camera becomes more popular since it can capture the relatively accurate color and depth information at the same time. With the recovered colorful point cloud, the traditional ICP (Iterative Closest Point) algorithm can be used to estimate the camera poses and reconstruct the scene. However, many works focus on improving ICP for processing the general scene and ignore the practical significance of effective initialization under the specific conditions, such as the indoor scene for VR or AR. In this work, a novel indoor prior based initialization method has been proposed to estimate the initial motion for ICP algorithm. We introduce the generation process of colorful point cloud at first, and then introduce the camera rotation initialization method for ICP in detail. A fast region growing based method is used to detect planes in an indoor frame. After we merge those small planes and pick up the two biggest unparallel ones in each frame, a novel rotation estimation method can be employed for the adjacent frames. We evaluate the effectiveness of our method by means of qualitative observation of reconstruction result because of the lack of the ground truth. Experimental results show that our method can not only fix the failure cases, but also can reduce the ICP iteration steps significantly.

This letter proposes a Light Space Partitioned Shadow Maps (LSPSMs) algorithm which implements shadow rendering based on a novel partitioning scheme in light space. In stead of splitting the view frustum like traditional Z-partitioning methods, we split partitions from the projection of refined view frustum in light space. The partitioning scheme is performed dual-directionally while limiting the wasted space. Partitions are created in dynamic number corresponding to the light and view directions. Experiments demonstrate that high quality shadows can be rendered in high efficiency with our algorithm.

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.

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.

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.

A non-linear extension of generalized hyperplane approximation (GHA) method is introduced in this letter. Although GHA achieved a high-confidence result in motion parameter estimation by utilizing the supervised learning scheme in histogram of oriented gradient (HOG) feature space, it still has unstable convergence range because it approximates the non-linear function of regression from the feature space to the motion parameter space as a linear plane. To extend GHA into a non-linear regression for larger convergence range, we derive theoretical equations and verify this extension's effectiveness and efficiency over GHA by experimental results.

Template tracking has been extensively studied in Computer Vision with a wide range of applications. A general framework is to construct a parametric model to predict movement and to track the target. The difference in intensity between the pixels belonging to the current region and the pixels of the selected target allows a straightforward prediction of the region position in the current image. Traditional methods track the object based on the assumption that the relationship between the intensity difference and the region position is linear or non-linear. They will result in bad tracking performance when just one model is adopted. This paper proposes a method, called as Mixture Hyperplanes Approximation, which is based on finite mixture of generalized linear regression models to perform robust tracking. Moreover, a fast learning strategy is discussed, which improves the robustness against noise. Experiments demonstrate the performance and stability of Mixture Hyperplanes Approximation.

Heterogeneous networks (HetNet) with different radio access technologies have been deployed to support a range of communication services. To manage these HetNets efficiently, some interworking solutions such as MIH (media independent handover), ANQP (access network query protocol) or ANDSF (access network discovery and selection function) have been studied. Recently, the millimeter-wave (mm-wave) based HetNet has been explored to provide multi-gigabits-per-second data rates over short distances in the 60GHz frequency band for 5G wireless networks. WiGig (Wireless Gigabit Alliance) is one of the available radio access technologies using mm-wave. However, the conventional interworking solutions are not sufficient for the implementation of LTE (Long Term Evolution)/WiGig HetNets. Since the coverage area of WiGig is very small due to the high propagation loss of the mm-wave band signal, it is difficult for UEs to perform cell discovery and handover if using conventional LTE/WLAN (wireless local area networks) interworking solutions, which cannot support specific techniques of WiGig well, such as beamforming and new media access methods. To solve these problems and find solutions for LTE/WiGig interworking, RAN (radio access network)-level tightly coupled interworking architecture will be a promising solution. As a RAN-level tightly coupled interworking solution, this paper proposes to design a LTE/WiGig protocol adaptor above the protocol stacks of WiGig to process and transfer control signaling and user data traffic. The proposed extended control plane can assist UEs to discover and access mm-wave BSs successfully and support LTE macro cells to jointly control the radio resources of both LTE and WiGig, so as to improve spectrum efficiency. The effectiveness of the proposal is evaluated. Simulation results show that LTE/WiGig HetNets with the proposed interworking solution can decrease inter-cell handover and improve user throughput significantly. Moreover, the downlink backhaul throughput and energy efficiency of mm-wave HetNets are evaluated and compared with that of 3.5GHz LTE HetNets. Results indicate that 60GHz mm-wave HetNets have better energy efficiency but with much heavier backhaul overhead.

This paper presents the detailed investigations on a simple multi-band method that allows inverted-F antennas (IFAs) to achieve good impedance matching in many different frequency bands. The impressive simplicity of the method arises from its sharing of a shorting strip among multiple branch elements to simultaneously generate independent resonant modes at arbitrary frequencies. Our simulation and measurement results clarify that, by adjusting the number of branch elements and their lengths, it is very easy to control both the total number of resonant modes and the position of each resonant frequency with impedance matching improved concurrently by adjusting properly the distance ds between the feeding and shorting points. The effectiveness of the multi-band method is verified in antenna miniaturization designs, not only in the case of handset antenna, but also in the design upon an infinite ground plane. Antenna performance and operation principles of proposed multi-band models in each case are analyzed and discussed in detail.

Recently, hue-preserving color image enhancement methods have been proposed by several researchers. However, the theoretical comparison of the performance of their methods has not been conducted yet. In this paper, we propose a hue-preserving saturation maximization method, and show a relationship of the saturation of enhanced colors by related methods. We also demonstrate the correctness of the relationship experimentally.

Performance suveyrance of CPML (Convolutional PML) for FDTD (Finite-Difference Time-Domain) method in cylindrical coordinate system was carried out. The CPML was placed perpendicularly to the radial axis and designed to absorb diverging or converging waves. To be able to analyze microstructured optical fibers and disk/ring resonators we introduced finite axial wavenumbers into the FDTD formulation. We investigated the dependence of reflectivity upon CPML's constituteve parameters such as $kappa$ and $sigma$ for various curvature radii and the axial wavenumbers. As a result of evaluation we found that the reflectivity gradually increased togather with the increase of the wavenumber. We also confirmed that the absorption performance was of the similar order for the converging waves and the diverging ones provided that their curvature radii were the same.

This paper proposes a so called quasi-linear support vector machine (SVM), which is an SVM with a composite quasi-linear kernel. In the quasi-linear SVM model, the nonlinear separation hyperplane is approximated by multiple local linear models with interpolation. Instead of building multiple local SVM models separately, the quasi-linear SVM realizes the multi local linear model approach in the kernel level. That is, it is built exactly in the same way as a single SVM model, by composing a quasi-linear kernel. A guided partitioning method is proposed to obtain the local partitions for the composition of quasi-linear kernel function. Experiment results on artificial data and benchmark datasets show that the proposed method is effective and improves classification performances.

This letter proposes an adaptive base plane filtering algorithm for the inter-plane estimation of RGB images in HEVC RExt. Because most high-frequency components of RGB images have low inter-plane correlation, our proposed scheme adaptively removes the high-frequency components of the base plane in order to enhance the inter-plane estimation accuracy. The experimental results show that the proposed scheme provides average BD rate gains of 0.6%, 1.0%, and 1.2% in the G, B, and R planes, respectively, with slightly decreased complexity, as compared to the previous inter-plane filtering method.

Mobile IPv6 is an IETF (Internet Engineering Task Force) standard which permits node mobility in IPv6. To manage mobility, it establishes a centralized mediator, Home Agent (HA), which inevitably introduces several penalties like triangular routing, single point of failure and limited scalability. Some later extensions such as Global HAHA, which employed multiple HAs, made to alleviate above shortcomings by introducing Distributed Mobility Management (DMM) approach. However, Multiple HA model will not be beneficial, unless the HAs are located finely. But, no major research paper has focused on locating HAs. This paper examines impact of single and multiple HA placements in data plane, by using an Autonomous System (AS) level topology consisting of 30,000 nodes with several evaluation criteria. All possible placements of HA(s) are analysed on a fair, random set of 30,000 node pairs of Mobile Nodes (MN) and Correspondent Nodes (CN). Ultimate result provides a concise account of different HA placements: i.e. cost centrality interprets performance variation better than degree centrality or betweenness. 30,000 ASs are classified into three groups in terms of Freeman's closeness index and betweenness centrality: 1) high range group, 2) mid range group, and 3) low range group. Considering dual HA placement, if one HA is placed in an AS in the high range group, then any subsequent HA placement gives worse results, thus single HA placement is adequate. With the mid range group, similar results are demonstrated by the upper portion of the group, but the rest yields better results when combined with another HA. Finally, from the perspective of low range group, if the subsequent HA is placed in the high range group, it gives better result. On the other hand, betweenness based grouping yields varying results. Consequently, this study reveals that the Freeman's closeness index is most appropriate in determining impacts of HA placements among considered indices.

In a convex drawing of a plane graph, all edges are drawn as straight-line segments without any edge-intersection and all facial cycles are drawn as convex polygons. In a convex grid drawing, all vertices are put on grid points. A plane graph G has a convex drawing if and only if G is internally triconnected, and an internally triconnected plane graph G has a convex grid drawing on an (n-1)×(n-1) grid if either G is triconnected or the triconnected component decomposition tree T(G) of G has two or three leaves, where n is the number of vertices in G. An internally triconnected plane graph G has a convex grid drawing on a 2n×2n grid if T(G) has exactly four leaves. In this paper, we show that an internally triconnected plane graph G has a convex grid drawing on a 6n×n2 grid if T(G) has exactly five leaves. We also present an algorithm to find such a drawing in linear time. This is the first algorithm that finds a convex grid drawing of such a plane graph G in a grid of polynomial size.

The uniform magnetic field of various strength was applied to the perpendicularly and in-plane demagnetized media, and the change in each magnetic cluster state was investigated as the fundamental investigation of the influence of demagnetization method on noise during signal recording on the stacked perpendicular recording media. The results showed that the in-plane demagnetization can achieve lower noise level if the recording field is not very high. In other words, the in-plane demagnetization is an effective way to achieve lower noise in transition area, near track edge of recorded bit, and in high-density bit. In addition, the simulation clarified that this noise reduction can be explained using the idea of sub-domain structure in the in-plane demagnetized media.

Electromagnetic power transmission through two cyl-inder-penetrated circular apertures in parallel conducting planes is studied. The Weber transform and superposition principle are used to represent the scattered field. A set of simultaneous equations for the modal coefficients are constituted based on the mode-matching and boundary conditions. The whole integration path is slightly deformed into a new one below the positive real axis not to pass through the pole singularities encountered on the original path so that it is easily calculated by direct numerical quadrature. Computation shows the behaviors of power transmission in terms of aperture geometry and wavelength. The presented scheme is very amenable to numerical evaluations and useful for various electromagnetic scattering and antenna radiation analysis involved with singularity problems.

In a sign-magnitude representation of binary lattice codevectors, only a few least significant bit-planes are constrained due to the structure of the lattice, while there is no restriction on other more significant bit-planes. Hence, any convenient bit-plane coding method can be used to encode the lattice codevectors, with modification required only for the lattice-defining, least-significant bit-planes. Simple encoding methods for the lattice-defining bit-planes of the D4, RE8, and Barnes-Wall 16-dimensional lattices are described. Simulation results for the encoding of a uniform source show that standard bit-plane coding together with the proposed encoding provide about the same performance as integer lattice vector quantization when the bit-stream is truncated. When the entire bit-stream is fully decoded, the granular gain of the lattice is realized.