Self-luminous light sources in the real world often have nonnegligible sizes and radiate light inhomogeneously. Acquiring the model of such a light source is highly important for accurate image synthesis and understanding. In this paper, we propose an approach to measuring 4D light fields of self-luminous extended light sources by using a liquid crystal (LC) panel, i.e. a programmable optical filter and a diffuse-reflection board. The proposed approach recovers the 4D light field from the images of the board illuminated by the light radiated from a light source and passing through the LC panel. We make use of the feature that the transmittance of the LC panel can be controlled both spatially and temporally. The approach enables multiplexed sensing and adaptive sensing, and therefore is able to acquire 4D light fields more efficiently and densely than the straightforward method. We implemented the prototype setup, and confirmed through a number of experiments that our approach is effective for modeling self-luminous extended light sources in the real world.

In this paper, we consider filter-and-forward relay beamforming using orthogonal frequency-division multiplexing (OFDM) in the presence of inter-block interference (IBI). We propose a filter design method based on a constrained max-min problem, which aims to suppress IBI and also avoid deep nulls in the frequency domain. It is shown that IBI can be suppressed completely owing to the employment of beamforming with multiple relays or multiple receive antennas at each relay when perfect channel state information (CSI) is available. In addition, we modify the proposed method to cover the case where only the partial CSI for relay-receiver channels is available. Numerical simulation results show that the proposed method significantly improves the performance as the number of relays and antennas increases due to spatial diversity, and the modified method can make use of the channel correlation to improve the performance.

This paper presents non-iterative cooperative/parallel Kalman filtering algorithms for decentralized network navigation, in which mobile nodes cooperate in both spatial and temporal domains to infer their positions. We begin by presenting an augmented minimum-mean-square error (MMSE) estimator for centralized navigation network, and then decouple it into a set of local sub-ones each corresponding to a mobile node; all these sub-estimators work in parallel and cooperatively — with the state estimates exchanging between neighbors — to provide results similar to those obtained by the augmented one. After that, we employ the approximation methods that adopted in the conventional nonlinear Kalman filters to calculate the second-order terms involved in these sub-estimators, and propose a decentralized cooperative/parallel Kalman filtering based network navigation framework. Finally, upon the framework, we present two cooperative/parallel Kalman filtering algorithms corresponding to the extended and unscented Kalman filters respectively, and compare them with conventional decentralized methods by simulations to show the superiority.

Due to the increasing demand for 3D video transmission over wireless networks, managing the quality of experience (QoE) of wireless 3D video clients is becoming increasingly important. However, the variability of compressed 3D video bit streams and the wireless channel condition as well as the complexity of 3D video viewing experience assessment make it difficult to properly allocate wireless transmission resources. In this paper, we discuss the characteristics of H.264 3D videos and QoE assessment of 3D video clients, and further propose a transmission scheme for 3D video transmission over a wireless communication system. The purpose of our scheme is to minimize the average ratio of stalls among all video streaming clients. By taking into account the playout lead and its change, we periodically evaluate the degree of urgency of each client as regards bitstream receipt based on fuzzy logic, and then allocate the transmission resource blocks to clients jointly considering their degrees of urgency and channel conditions. The adaptive modulation and coding scheme (MCS) is applied to ensure a low transmission error rate. Our proposed scheme is suitable for practical implementation since it has low complexity, and can be easily applied in 2D video transmission and in non-OFDM systems. Simulation results, based on three left-and-right-views 3D videos and the Long Term Evolution (LTE) system, demonstrate the validity of our proposed scheme.

Quadriphase sequences with good correlation properties are required in higher order digital modulation schemes, e.g., for timing measurements, channel estimation or synchronization. In this letter, based on interleaving technique and pairs of mismatched binary sequences with perfect cross-correlation function (PCCF), two new methods for constructing quadriphase sequences with mismatched filtering which exist for even length N ≡ 2(mod4) are presented. The resultant perfect mismatched quadriphase sequences have high energy efficiencies. Compared with the existing methods, the new methods have flexible parameters and can give cyclically distinct perfect mismatched quadriphase sequences.

This letter presents a simple and explicit formulation of non-unique Wiener filters associated with the linear predictor for processing of sinusoids. It was shown in the literature that, if the input signal consists of only sinusoids and does not include a white noise, the input autocorrelation matrix in the Wiener-Hopf equation becomes rank-deficient and thus the Wiener filter is not uniquely determined. In this letter we deal with this rank-deficient problem and present a mathematical description of non-unique Wiener filters in a simple and explicit form. This description is directly obtained from the tap number, the frequency of sinusoid, and the delay parameter. We derive this result by means of the elementary row operations on the augmented matrix given by the Wiener-Hopf equation. We also show that the conventional Wiener filter for noisy input signal is included as a special case of our description.

This study investigates a real-time joint channel and hyperparameter estimation method for orthogonal frequency division multiplexing mobile communications. The channel frequency response of the pilot subcarrier and its fixed hyperparameters (such as channel statistics) are estimated using a Liu and West filter (LWF), which is based on the state-space model and sequential Monte Carlo method. For the first time, to our knowledge, we demonstrate that the conventional LWF biases the hyperparameter due to a poor estimate of the likelihood caused by overfitting in noisy environments. Moreover, this problem cannot be solved by conventional smoothing techniques. For this, we modify the conventional LWF and regularize the likelihood using a Kalman smoother. The effectiveness of the proposed method is confirmed via numerical analysis. When both of the Doppler frequency and delay spread hyperparameters are unknown, the conventional LWF significantly degrades the performance, sometimes below that of least squares estimation. By avoiding the hyperparameter estimation failure, our method outperforms the conventional approach and achieves good performance near the lower bound. The coding gain in our proposed method is at most 10 dB higher than that in the conventional LWF. Thus, the proposed method improves the channel and hyperparameter estimation accuracy. Derived from mathematical principles, our proposal is applicable not only to wireless technology but also to a broad range of related areas such as machine learning and econometrics.

Many research efforts are being focused upon the design of dynamic Inter-Cell Interference Coordination (ICIC) schemes for macrocell/picocell heterogeneous networks employing Cell Range Expansion (CRE). In order to protect the expanded Pico User Equipments (ePUEs) located in the CRE region from severe Macro Base Station (MBS) interference in downlink, the conventional methods reduce the transmit power of the MBS in the Almost Blank Subframes (ABSs), where ePUEs can be scheduled. However, this severely limits the amount of usable resources/power for the MBS as compared to Resource Block (RB)-based dynamic allocation. Instead, we propose a self-organized RB-based dynamic resource allocation method. Based on the proposed partial Channel State Information (CSI) sharing, the MBS obtains ePUEs' CSI and predicts their RB allocation. Then, the MBS reduces its transmit power in RBs where the ePUEs' allocation probability is estimated to be high. The simulation results show that the proposed scheme achieves excellent macrocell/picocell performance trade-offs, even when taking into account the overhead increase due to the partial CSI sharing.

An efficient Monte Carlo (MC) method for the calculation of failure probability degradation of an SRAM cell due to negative bias temperature instability (NBTI) is proposed. In the proposed method, a particle filter is utilized to incrementally track temporal performance changes in an SRAM cell. The number of simulations required to obtain stable particle distribution is greatly reduced, by reusing the final distribution of the particles in the last time step as the initial distribution. Combining with the use of a binary classifier, with which an MC sample is quickly judged whether it causes a malfunction of the cell or not, the total number of simulations to capture the temporal change of failure probability is significantly reduced. The proposed method achieves 13.4× speed-up over the state-of-the-art method.

The High efficiency video coding (HEVC) standard defines two in-loop filters to improve the objective and subjective quality of the reconstructed frames. Through analyzing the effectiveness of the in-loop filters, it is noted that band offset (BO) process achieves much more coding gains for text region which mostly employ intra block copy (IntraBC) prediction mode. The intraBC prediction process in HEVC is performed by using the already reconstructed region for block matching, which is similar to motion compensation. If BO process is applied after one coding tree unit (CTU) encoded, the distortion between original and reconstructed samples copied by the IntraBC prediction will be further reduced, which is simple to operate and can obtain good coding efficiency. Experimental results show that the proposed scheme achieves up to 3.4% BD-rate reduction in All-intra (AI) for screen content sequences with encoding and decoding time no increase.

A novel rendering algorithm with a best-matching patch is proposed to address the noise artifacts associated with Monte Carlo renderings. First, in the sampling stage, the representative patch is selected through a modified patch shift procedure, which gathers homogeneous pixels together to stay clear of the edges. Second, each pixel is filtered over a discrete set of filters, where the range kernel is computed using the selected patches. The difference between the selected patch and the filtered value is used as the pixel error, and the single filter that returns the smallest estimated error is chosen. In the reconstruction stage, pixel colors are combined with features of depth, normal and texture to form a cross bilateral filter, which highly preserves scene details while effectively removing noise. Finally, a heuristic metric is calculated to allocate additional samples in difficult regions. Compared with state-of-the art methods, the proposed algorithm performs better both in visual image quality and numerical error.

In this paper, a multiple-object tracking approach in large-scale scene is proposed based on visual sensor network. Firstly, the object detection is carried out by extracting the HOG features. Then, object tracking is performed based on an improved particle filter method. On the one hand, a kind of temporal and spatial dynamic model is designed to improve the tracking precision. On the other hand, the cumulative error generated from evaluating particles is eliminated through an appearance model. In addition, losses of the tracking will be incurred for several reasons, such as occlusion, scene switching and leaving. When the object is in the scene under monitoring by visual sensor network again, object tracking will continue through object re-identification. Finally, continuous multiple-object tracking in large-scale scene is implemented. A database is established by collecting data through the visual sensor network. Then the performances of object tracking and object re-identification are tested. The effectiveness of the proposed multiple-object tracking approach is verified.

This paper proposes a new design formula of coupling coefficient between antenna and resonator for an efficient design of filtering antennas consisting of an antenna and resonators. The filtering antenna can be designed by introducing a well-established filter design theory. For such a design approach, an external Q factor at input port, coupling coefficients, and a radiation Q factor of the antenna need to be evaluated. However, conventional design methods have a time-consuming procedure, since there are no effective techniques to evaluate the coupling coefficient between resonator and antenna. To solve the problem, we derive the new design formula using only amplitude property of input reflection responses obtained from a coupled structure of resonator and antenna. As an example, a third-order filtering antenna is synthesized, designed, and tested at 2.45 GHz, which numerically and experimentally validates the effectiveness of the derived equation.

A triplexer is presented by using bandpass filters (BPFs) which consist of two-stage of wideband resonator and additional open-circuited stubs. The resonator is firstly proposed by using a coupled-line and an inductive element loaded transmission line. This resonator produces the wide passband by a dual-mode resonance, high attenuation level at stopbands, and the steepness at the edge of the passband due to the attenuation poles. In order to understand the behavior of the resonator, the conditions for resonances and attenuation poles are especially solved and their current densities are analyzed by an electromagnetic simulation. Secondly, three types of wideband BPFs are constituted and finally a wideband triplexer is composed by using these BPFs. The basic characteristics of the proposed BPFs and the matching methodology enable to realize the triplexer whose desired passbands are around 3.1-5.1 GHz, 5.85-7.85 GHz, and 8.6-10.6 GHz with high isolation performance at the other passbands. The proposed triplexer is predominance in the flexible bandwidth or wide operating frequency range. All the BPFs and the triplexer are implemented on a planar printed circuit board assuming the use of the microstrip line structure.

A compact millimeter-wave three-pole dual-band bandpass filter (BPF) by using substrate-integrated waveguide (SIW) dual-mode cavities is developed in this paper. The proposed filter consists of three SIW dual-mode cavities, in which the TE201 and TE102 modes are used to form two passbands. The center frequencies of the two passbands can be readily changed by varying the lengths and/or widths of the SIW cavities. Meanwhile three transmission zeros are produced with appropriate design of the input and output of the SIW cavities, which increase significantly the isolation between the two passbands and their roll-off rate of attenuations. The dual-band BPF filter is designed, fabricated and measured. The measured center frequencies of the two passbands are 26.75GHz and 31.55GHz, respectively. The 3dB-passbands are 26.35-27.15GHz (3%) and 31.29-31.81GHz (1.6%), respectively, with maximum insertion loss of 2.64dB and 4.2dB, respectively, and return loss larger than 12dB in both passbands. A good agreement between the simulated and measured filter characteristics is obtained.

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.

We have proposed and demonstrated the principle of optical mode switch. However, the crosstalk between modes has not yet reported due to the difficulty of mode recognition and distinction. To accomplish this mode crosstalk evaluation, we integrated multimode interference (MMI) mode filter with the optical mode switch in this work. As a result, for the both TE and TM modes, the crosstalk of approximately -10 dB has been evaluated experimentally.

Visual tracking has been studied for several decades but continues to draw significant attention because of its critical role in many applications. Recent years have seen greater interest in the use of correlation filters in visual tracking systems, owing to their extremely compelling results in different competitions and benchmarks. However, there is still a need to improve the overall tracking capability to counter various tracking issues, including large scale variation, occlusion, and deformation. This paper presents an appealing tracker with robust scale estimation, which can handle the problem of fixed template size in Kernelized Correlation Filter (KCF) tracker with no significant decrease in the speed. We apply the discriminative correlation filter for scale estimation as an independent part after finding the optimal translation based on the KCF tracker. Compared to an exhaustive scale space search scheme, our approach provides improved performance while being computationally efficient. In order to reveal the effectiveness of our approach, we use benchmark sequences annotated with 11 attributes to evaluate how well the tracker handles different attributes. Numerous experiments demonstrate that the proposed algorithm performs favorably against several state-of-the-art algorithms. Appealing results both in accuracy and robustness are also achieved on all 51 benchmark sequences, which proves the efficiency of our tracker.

A novel scheme to implement a filter bank multicarrier/offset quadrature amplitude modulation (FBMC/OQAM) transmission system is proposed. This is achieved by replacing the existing polyphase filter banks based on FFT/IFFT with fast filter bank (FFB) in order to utilize its good properties such as cascaded structure and high frequency selectivity with a comparable complexity as FFT/IFFT. Although this topic is not addressed in the literature, the impulse response of the prototype filter for each stage within FFB can still be obtained by using an optimization technique, which is used to minimize the distortion caused by intersymbol and interchannel interferences (ISI and ICI) of the proposed FBMC/OQAM transmission system, subject to allowable ripples in the passband and stopband. As a result, the relationship between two-path prototype filters in each subfilter should be modified with a general form accordingly. Simulations show that the number of multiplications required by the proposed scheme is smaller than that needed by the polyphase filter banks solution based on FFT/IFFT. Furthermore, the suitability of the design of prototype filters and the validation can be also supported by the results.

User-based and item-based collaborative filtering (CF) are two of the most important and popular techniques in recommender systems. Although they are widely used, there are still some limitations, such as not being well adapted to the sparsity of data sets, failure to consider the hierarchical structure of the items, and changes in users' interests when calculating the similarity of items. To overcome these shortcomings, we propose an evolutionary approach based on hierarchical structure for dynamic recommendation system named Hierarchical Temporal Collaborative Filtering (HTCF). The main contribution of the paper is displayed in the following two aspects. One is the exploration of hierarchical structure between items to improve similarity, and the other is the improvement of the prediction accuracy by utilizing a time weight function. A unique feature of our method is that it selects neighbors mainly based on hierarchical structure between items, which is more reliable than co-rated items utilized in traditional CF. To the best of our knowledge, there is little previous work on researching CF algorithm by combining object implicit or latent object-structure relations. The experimental results show that our method outperforms several current recommendation algorithms on recommendation accuracy (in terms of MAE).