In this work, two new proposed NMF models are developed for facial expression recognition. They are called maximum volume constrained nonnegative matrix factorization (MV_NMF) and maximum volume constrained graph nonnegative matrix factorization (MV_GNMF). They achieve sparseness from a larger simplicial cone constraint and the extracted features preserve the topological structure of the original images.

In this letter, we analyze performances of a frequency offset estimation based on the maximum likelihood criterion and provide a theoretical proof that the mean squared error of the estimation grows with increase in the offset. Moreover, we propose a new iterative offset estimation method based on the analysis. By computer simulations, we show that the proposed estimator can achieve the lowest estimation error after a few iterations.

This paper presents a strategy, Weighted Voting of Discriminative Regions (WVDR), to improve the face recognition performance, especially in Small Sample Size (SSS) and occlusion situations. In WVDR, we extract the discriminative regions according to facial key points and abandon the rest parts. Considering different regions of face make different contributions to recognition, we assign weights to regions for weighted voting. We construct a decision dictionary according to the recognition results of selected regions in the training phase, and this dictionary is used in a self-defined loss function to obtain weights. The final identity of test sample is the weighted voting of selected regions. In this paper, we combine the WVDR strategy with CRC and SRC separately, and extensive experiments show that our method outperforms the baseline and some representative algorithms.

This paper describes the background noise estimation technique of the tensor product expansion with absolute error (TPE-AE) to estimate multiple sources. The electroencephalogram (EEG) signal produced by the saccadic eye movement is adopted to analyze relationship between a brain function and a human activity. The electrooculogram (EOG) generated by eye movements yields significant problems for the EEG analysis. The denoising of EOG artifacts is important task to perform an accurate analysis. In this paper, the two types of TPE-AE are proposed to estimates EOG and other components in EEG during eye movement. One technique estimates two outer products using median filter based TPE-AE. The another technique uses a reference signal to separate the two sources. We show that the proposed method is effective to estimate and separate two sources in EEG.

High-dynamic-range imaging (HDRI) technologies aim to extend the dynamic range of luminance against the limitation of camera sensors. Irradiance information of a scene can be reconstructed by fusing multiple low-dynamic-range (LDR) images with different exposures. The key issue is removing ghost artifacts caused by motion of moving objects and handheld cameras. This paper proposes a robust ghost-free HDRI algorithm by visual salience based bilateral motion detection and stack extension based exposure fusion. For ghost areas detection, visual salience is introduced to measure the differences between multiple images; bilateral motion detection is employed to improve the accuracy of labeling motion areas. For exposure fusion, the proposed algorithm reduces the discontinuity of brightness by stack extension and rejects the information of ghost areas to avoid artifacts via fusion masks. Experiment results show that the proposed algorithm can remove ghost artifacts accurately for both static and handheld cameras, remain robust to scenes with complex motion and keep low complexity over recent advances including rank minimization based method and patch based method by 63.6% and 20.4% time savings averagely.

For ternary system, both anionic carboxylate ligand, namely, 4,4'-oxybis(benzoic acid)(H2oba) and different auxiliary ligand, namely, 1,10-phenanthroline(Phen), pyrazino[2,3-f][1,10]phenanthroline (dpq) and 1H-imidazole[2,3-f][1,10]phenanthroline(IP) have been designed and employed for the construction of a series of lanthanide compounds (Tb3+, Eu3+). The results of photoluminescence spectra of the compounds show the different optimal excitation spectra that make it closer to UV/Blue range.

In this letter, we propose a robust and fast tracking framework by combining local and global appearance models to cope with partial occlusion and pose variations. The global appearance model is represented by a correlation filter to efficiently estimate the movement of the target and the local appearance model is represented by local feature points to handle partial occlusion and scale variations. Then global and local appearance models are unified via the Bayesian inference in our tracking framework. We experimentally demonstrate the effectiveness of the proposed method in both terms of accuracy and time complexity, which takes 12ms per frame on average for benchmark datasets.

This study involves proposing a high-speed computer-generated hologram playback by using a digital micromirror device for high-definition spatiotemporal division multiplexing electroholography. Consequently, the results indicated that the study successfully reconstructed a high-definition 3-D movie of 3-D objects that was comprised of approximately 900,000 points at 60 fps when each frame was divided into twelve parts.

This paper presents an interactive locomotion controller using motion capture data and an inverted pendulum model (IPM). The motion data of a character is decomposed into those of upper and lower bodies, which are then dimension-reduced via what we call hierarchical Gaussian process dynamical model (H-GPDM). The locomotion controller receives the desired walking direction from the user. It is integrated into the IPM to determine the pose of the center of mass and the stance-foot position of the character. They are input to the H-GPDM, which interpolates the low-dimensional data to synthesise a redirected motion sequence on an uneven surface. The locomotion controller allows the upper and lower bodies to be independently controlled and helps us generate natural locomotion. It can be used in various real-time applications such as games.

For mobile video codecs, the huge energy dissipation for external memory traffic is a critical challenge under the battery power constraint. Lossy embedded compression (EC), as a solution to this challenge, is considered in this paper. While previous studies in lossy EC mostly focused on algorithm optimization to reduce distortion, this work, to the best of our knowledge, is the first one that addresses the distortion control. Firstly, from both theoretical analysis and experiments for distortion optimization, a conclusion is drawn that, at the frame level, allocating memory traffic evenly is a reliable approximation to the optimal solution to minimize quality loss. Then, to reduce the complexity of decoding twice, the distortion between two sequences is estimated by a linear function of that calculated within one sequence. Finally, on the basis of even allocation, the distortion control is proposed to determine the amount of memory traffic according to a given distortion limitation. With the adaptive target setting and estimating function updating in each group of pictures (GOP), the scene change in video stream is supported without adding a detector or retraining process. From experimental results, the proposed distortion control is able to accurately fix the quality loss to the target. Compared to the baseline of negative feedback on non-referred B frames, it achieves about twice memory traffic reduction.

Bloom Filter is a bit array (a one-dimensional storage structure) that provides a compact representation for a set of data, which can be used to answer the membership query in an efficient manner with a small number of false positives. It has a lot of applications in many areas. In this paper, we extend the design of Bloom Filter by using a multi-dimensional matrix to replace the one-dimensional structure with three different implementations, namely OFFF, WOFF, FFF. We refer the extended Bloom Filter as Feng Filter. We show the false positive rates of our method. We compare the false positive rate of OFFF with that of the traditional one-dimensional Bloom Filter and show that under certain condition, OFFF has a lower false positive rate. Traditional Bloom Filter can be regarded as a special case of our Feng Filter.

Several kinds of techniques for excellent multi-user interference (MUI) cancellation have been proposed for direct-detection synchronous optical code division multiple access (OCDMA) systems. All these techniques utilize modified prime sequence codes (MPSCs) as signature codes and can remove MUI errors efficiently. In this paper, the features of three typical MUI cancellers are studied and compared in detail. The authors defined the parameter “decision distance” to show the feature of MUI cancellers. The bit error rate performance of each canceller is investigated by computer simulation and compared with that of the basic on-off keying (OOK) scheme without cancellation. Then, we investigate the relationship between the decision distance and the bit error rate performance. It is shown that every canceller has a better bit error rate performance than the basic OOK scheme. Especially, the equal weight orthogonal (EWO) scheme, whose decision distance is the largest, has the best error resistance property of the three MUI cancellers. The results show that the decision distance is a useful index to evaluate the error resistance property of MUI cancellation schemes.

We newly propose the first lateral mode selective active multimode interferometer laser diode. The design principle is to arrange identical propagation path of different lateral mode. Thanks to multimode waveguide structure, 0th mode and 1st order mode has individual propagation path within one device. Individual lasing of fundamental mode as well as first mode was confirmed successfully.

In this paper, we propose a design method of compact multi-way Wilkinson power divider with a multiband operation for size reduction and band broadening. The proposed divider consists of multisection LC-ladder circuits in the division arms and isolation circuits between the output ports. To validate design procedures, we fabricated a trial divider at VHF band. The circuit layout of the trial divider was decided by using an electromagnetic simulator (Sonnet EM). Because the proposed divider consists of lumped element circuits, we can realize great miniaturization of a circuit area compared to that of the conventional Wilkinson power divider. The circuit size of the trial divider is 35 mm square. The measurement results for the trial divider by using a vector network analyzer indicates a relative bandwidth of about 60% under -17 dB reflection, flat power division within ±0.1 dB, and very low phase imbalances under 1.0 degree over the wide frequency range.

A novel generalized side-information cancellation (GSIC) precoder is proposed for multiuser multi-input multi-output (MIMO) downlink systems with channel state information at the transmitter. The proposed transceiver involves the following stages. First, a minimum mean square error (MMSE) based channel inversion (MMSE-CI) technique is utilized to suppress multiuser broadcast interference. By using a GSIC technique, it can further reduce the residual multiuser interference and the noise induced by MMSE-CI preprocessing. Next, with a singular value decomposition method, the spatial stream interference of each user is suppressed by the pre-processing and post-processing eigenvector matrices. Finally, the proposed precoder can be extended to joint water filling and diagonal loading methods for performance enhancement. For the correlated MIMO channels, signal subspace and antenna selection methods, incorporating the proposed GSIC precoder, are further designed to maximize the sum rate performance. Simulation results show that the proposed GSIC precoder outperforms the conventional precoders. Besides, simulation results confirm that the proposed GSIC precoder with water filling, diagonal loading, and signal subspace techniques exhibits excellent performance.

Multi-label classification is an appealing and challenging supervised learning problem, where multiple labels, rather than a single label, are associated with an unseen test instance. To remove possible noises in labels and features of high-dimensionality, multi-label dimension reduction has attracted more and more attentions in recent years. The existing methods usually suffer from several problems, such as ignoring label outliers and label correlations. In addition, most of them emphasize on conducting dimension reduction in an unsupervised or supervised way, therefore, unable to utilize the label information or a large amount of unlabeled data to improve the performance. In order to cope with these problems, we propose a novel method termed Robust sEmi-supervised multi-lAbel DimEnsion Reduction, shortly READER. From the viewpoint of empirical risk minimization, READER selects most discriminative features for all the labels in a semi-supervised way. Specifically, the ℓ2,1-norm induced loss function and regularization term make READER robust to the outliers in the data points. READER finds a feature subspace so as to keep originally neighbor instances close and embeds labels into a low-dimensional latent space nonlinearly. To optimize the objective function, an efficient algorithm is developed with convergence property. Extensive empirical studies on real-world datasets demonstrate the superior performance of the proposed method.

This paper proposes a new methodology to design optimal antennas for MIMO (Multi-Input Multi-Output) communication systems by using spherical mode expansion. Given spatial channel properties of a MIMO channel, such as the angular profile at both sides, the optimal MIMO antennas should provide the largest channel capacity with a constraint of the limited implementation space (volume). In designing a conventional MIMO antenna, first the antenna structure (current distribution) is determined, second antenna directivity is calculated based on the current distribution, and thirdly MIMO channel capacity is calculated by using given angular profiles and obtained antenna directivity. This process is repeated by adjusting the antenna structure until the performance satisfies a predefined threshold. To the contrary, this paper solves the optimization problem analytically and finally gives near optimal antenna structure (current distribution) without any greedy search. In the proposed process, first the optimal directivity of MIMO antennas is derived by applying spherical mode expansion to the angular profiles, and second a far-near field conversion is applied on the derived optimal directivity to achieve near optimal current distributions on a limited surface. The effectiveness of the proposed design methodology is validated via numerical calculation of MIMO channel capacity as in the conventional design method while giving near optimal current distribution with constraint of an antenna structure derived from proposed methodology.

This paper proposes a method for human pose estimation in still images. The proposed method achieves occlusion-aware appearance modeling. Appearance modeling with less accurate appearance data is problematic because it adversely affects the entire training process. The proposed method evaluates the effectiveness of mitigating the influence of occluded body parts in training sample images. In order to improve occlusion evaluation by a discriminatively-trained model, occlusion images are synthesized and employed with non-occlusion images for discriminative modeling. The score of this discriminative model is used for weighting each sample in the training process. Experimental results demonstrate that our approach improves the performance of human pose estimation in contrast to base models.

To suppress intercell interference for three-cell half-duplex relay systems, joint interference suppression and multiuser detection (MUD) schemes that estimate weight coefficients by the recursive least-squares (RLS) algorithm have been proposed but show much worse bit error rate (BER) performance than maximum likelihood detection (MLD). To improve the BER performance, this paper proposes a joint interference suppression and MUD scheme that estimates the weight coefficients by eigenvalue decomposition. The proposed scheme carries the same advantages as the conventional RLS based schemes; it does not need channel state information (CSI) feedback while incurring much less amount of computational complexity than MLD. In addition, it needs to know only two out of three preambles used in the system. Computer simulations of orthogonal frequency-division multiplexing (OFDM) transmission under three-cell and frequency selective fading conditions are conducted. It is shown that the eigendecomposition-based scheme overwhelmingly outperforms the conventional RLS-based scheme although requiring higher computational complexity.

A single-dimensional interface which enables users to obtain diverse localizations of audio sources is proposed. In many conventional interfaces for arranging audio sources, there are multiple arrangement parameters, some of which allow users to control positions of audio sources. However, it is difficult for users who are unfamiliar with these systems to optimize the arrangement parameters since the number of possible settings is huge. We propose a simple, single-dimensional interface for adjusting arrangement parameters, allowing users to sample several diverse audio source arrangements and easily find their preferred auditory localizations. To select subsets of arrangement parameters from all of the possible choices, auditory-localization space vectors (ASVs) are defined to represent the auditory localization of each arrangement parameter. By selecting subsets of ASVs which are approximately orthogonal, we can choose arrangement parameters which will produce diverse auditory localizations. Experimental evaluations were conducted using music composed of three audio sources. Subjective evaluations confirmed that novice users can obtain diverse localizations using the proposed interface.