A discriminative reference-based method for scene image categorization is presented in this letter. Reference-based image classification approach combined with K-SVD is approved to be a simple, efficient, and effective method for scene image categorization. It learns a subspace as a means of randomly selecting a reference-set and uses it to represent images. A good reference-set should be both representative and discriminative. More specifically, the reference-set subspace should well span the data space while maintaining low redundancy. To automatically select reference images, we adapt affinity propagation algorithm based on data similarity to gather a reference-set that is both representative and discriminative. We apply the discriminative reference-based method to the task of scene categorization on some benchmark datasets. Extensive experiment results demonstrate that the proposed scene categorization method with selected reference set achieves better performance and higher efficiency compared to the state-of-the-art methods.

In Still-to-Video (S2V) face recognition, only a few high resolution images are registered for each subject, while the probe is video clips of complex variations. As faces present distinct characteristics under different scenarios, recognition in the original space is obviously inefficient. Thus, in this paper, we propose a novel discriminant analysis method to learn separate mappings for different scenario patterns (still, video), and further pursue a common discriminant space based on these mappings. Concretely, by modeling each video as a manifold and each image as point data, we form the scenario-oriented mapping learning as a Point-Manifold Discriminant Analysis (PMDA) framework. The learning objective is formulated by incorporating the intra-class compactness and inter-class separability for good discrimination. Experiments on the COX-S2V dataset demonstrate the effectiveness of the proposed method.

Local descriptors, Local Binary Pattern (LBP) and Scale Invariant Feature Transform (SIFT) are widely used in various computer applications. They emphasize different aspects of image contents. In this letter, we propose to combine them in sparse coding for categorizing scene images. First, we regularly extract LBP and SIFT features from training images. Then, corresponding to each feature, a visual word codebook is constructed. The obtained LBP and SIFT codebooks are used to create a two-dimensional table, in which each entry corresponds to an LBP visual word and a SIFT visual word. Given an input image, LBP and SIFT features extracted from the same positions of this image are encoded together based on sparse coding. After that, spatial max pooling is adopted to determine the image representation. Obtained image representations are converted into one-dimensional features and classified by utilizing SVM classifiers. Finally, we conduct extensive experiments on datasets of Scene Categories 8 and MIT 67 Indoor Scene to evaluate the proposed method. Obtained results demonstrate that combining features in the proposed manner is effective for scene categorization.

Wide area virtualization of wireless transceivers by centrally managed software radio systems is a way to efficiently share the resources for supporting a variety of wireless protocols. In order to enable wide-area virtualization of wireless transceivers, the authors have developed a mechanism to deliver the radio space information which is quantized broadband radio wave information including the radio signals to the transceivers. Delivery mechanism consists of a distribution server which distributes radio space corresponding to the request of the client such as the center frequency and the bandwidth and a client which uses the radio space information. Accumulation of the distribution servers which deliver radio space information simultaneously to a large number of clients will contribute to build an infrastructure for any clients ubiquitously distributed over the globe. In this paper, scale-out architecture of a distribution server is proposed to deliver unlimitedly broadband radio space information to unlimited number of clients. Experimental implementation indicates the architecture to be a scale-out solution, while the number of clients is restricted by the computer resources of the distribution server. The band pass filter processing for individual client in the distribution server consumes the dominant part of the processing power, and the number of CPU cores is the upper limit of clients supportable for the distribution server in the current operating system implementation. The logical increase of the number of CPU cores by hardware multithreading does not contribute to relax this limit. We also discuss the guidance architecture or building server derived from these conclusions.

This paper tries to model spatial layout beyond the traditional spatial pyramid (SP) in the coding/pooling scheme for scene text character recognition. Specifically, we propose a novel method to build a dictionary called spatiality embedded dictionary (SED) in which each codeword represents a particular character stroke and is associated with a local response region. The promising results outperform other state-of-the-art algorithms.

For the past couple of decades, the usage of the Web as a platform for deploying software products has become incredibly popular. Web applications became more prevalent, as well as more complex. Countless Web applications have already been designed, developed, tested, and deployed on the Internet. However, it is noticeable that many common functionalities are present among these vast number of applications. This paper proposes an approach based on a database containing information from previous test artifacts. The information is used to generate test scenarios for Web applications under test. We have developed a tool based on our proposed approach, with the aim of reducing the effort required from software test engineers and professionals during the test planning and creation stage of software engineering. We evaluated our approach from three viewpoints: comparison between our approach and manual generation, qualitative evaluation by professional software engineers, and comparison between our approach and two open-source tools.

Numerous studies have been focusing on the improvement of bag of features (BOF), histogram of oriented gradient (HOG) and scale invariant feature transform (SIFT). However, few works have attempted to learn the connection between them even though the latter two are widely used as local feature descriptor for the former one. Motivated by the resemblance between BOF and HOG/SIFT in the descriptor construction, we improve the performance of HOG/SIFT by a) interpreting HOG/SIFT as a variant of BOF in descriptor construction, and then b) introducing recently proposed approaches of BOF such as locality preservation, data-driven vocabulary, and spatial information preservation into the descriptor construction of HOG/SIFT, which yields the BOF-driven HOG/SIFT. Experimental results show that the BOF-driven HOG/SIFT outperform the original ones in pedestrian detection (for HOG), scene matching and image classification (for SIFT). Our proposed BOF-driven HOG/SIFT can be easily applied as replacements of the original HOG/SIFT in current systems since they are generalized versions of the original ones.

As one of organic electroluminescent (EL) materials, we developed a method of fabricating an ink using low molecular- weight materials with a long emission lifetime for application to the inkjet method. Although the emission lifetime is usually long for low molecular-weight materials, their high manufacturing cost due to the necessity of vapor deposition is a disadvantage. We utilized the low molecular-weight material, tris-(8-hydroxyquinoline) aluminum (Alq3), and investigated its dispersibility in a solvent in which it has low solubility. In addition, we ascertained whether the material could maintain its photoluminescence characteristic under the irradiation of ultraviolet rays by investigating the emission of photoluminescence. Alq3 was crystallized into nanosize crystals, whose surface was then coated with a primary amine by the gas evaporation method. The fabricated ink contained crystals with an average size of 250nm and high dispersibility in tetradecane, in which Alq3 is insoluble. Thus, we made it possible to carry out an inkjet method with low molecular weight EL materials.

An amplitude shift keying transmitter and receiver chipset with low power consumption using 40nm CMOS technology for wireless communication systems is described, in which a maximum data rate of 10Gbps and power consumption of 98.4mW are obtained with a carrier frequency of 135GHz. A simple circuit and a modulation method to reduce power consumption are selected for the chipsets. To realize multi-gigabit wireless communication, the receiver is designed considering the group delay optimization. In the receiver design, the low-noise amplifier and detector are designed considering the total optimization of the gain and group delay in the millimeter-wave modulated signal region.

This paper presents a GPU (Graphics Processing Units) implementation of dynamic programming for the optimal polygon triangulation. Recently, GPUs can be used for general purpose parallel computation. Users can develop parallel programs running on GPUs using programming architecture called CUDA (Compute Unified Device Architecture) provided by NVIDIA. The optimal polygon triangulation problem for a convex polygon is an optimization problem to find a triangulation with minimum total weight. It is known that this problem for a convex n-gon can be solved using the dynamic programming technique in O(n3) time using a work space of size O(n2). In this paper, we propose an efficient parallel implementation of this O(n3)-time algorithm on the GPU. In our implementation, we have used two new ideas to accelerate the dynamic programming. The first idea (adaptive granularity) is to partition the dynamic programming algorithm into many sequential kernel calls of CUDA, and to select the best parameters for the size and the number of blocks for each kernel call. The second idea (sliding and mirroring arrangements) is to arrange the working data for coalesced access of the global memory in the GPU to minimize the memory access overhead. Our implementation using these two ideas solves the optimal polygon triangulation problem for a convex 8192-gon in 5.57 seconds on the NVIDIA GeForce GTX 680, while a conventional CPU implementation runs in 1939.02 seconds. Thus, our GPU implementation attains a speedup factor of 348.02.

To handle the variety of scene characters, we propose a cooperative multiple-hypothesis framework which consists of an image operator set module, an Optical Character Recognition (OCR) module and an integration module. Multiple image operators activated by multiple parameters probe suspected character regions. The OCR module is then applied to each suspected region and returns multiple candidates with weight values for future integration. Without the aid of the heuristic rules which impose constraints on segmentation area, aspect ratio, color consistency, text line orientations, etc., the integration module automatically prunes the redundant detection/recognition and pads the missing detection/recognition. The proposed framework bridges the gap between scene character detection and recognition, in the sense that a practical OCR engine is effectively leveraged for result refinement. In addition, the proposed method achieves the detection and recognition at the character level, which enables dealing with special scenarios such as single character, text along arbitrary orientations or text along curves. We perform experiments on the benchmark ICDAR 2011 Robust Reading Competition dataset which includes a text localization task and a word recognition task. The quantitative results demonstrate that multiple hypotheses outperform a single hypothesis, and be comparable with state-of-the-art methods in terms of recall, precision, F-measure, character recognition rate, total edit distance and word recognition rate. Moreover, two additional experiments are conducted to confirm the simplicity of parameter setting in this proposal.

A plane coupler has been developed for a two-dimensional (2D) wireless power transmission. This coupler can construct a continuous wireless power transmission system for mobile devices due to its small, light characteristics. This coupler has two elements connected with a 2D waveguide sheet, and coupling capacitances between the elements and the sheet decrease the coupler size by reducing their resonance frequencies. A propagation loss of -10.0 dB is obtained using the small 0.025-λ2 coupler. Continuous operation of the mobile device is demonstrated by applying wireless power transmission to the 2D waveguide sheet with the small plane coupler.

For the problem of Indoor Home Scene Classification, this paper proposes the BOW Model of Local Feature Information Gain. The experimental results show that not only the performance is improved but also the computation is reduced. Consequently this method out performs the state-of-the-art approach.

This paper presents a novel scale-rotation invariant generative model (SRIGM) and a kernel sparse representation classification (KSRC) method for scene categorization. Recently the sparse representation classification (SRC) methods have been highly successful in a number of image processing tasks. Despite its popularity, the SRC framework lucks the abilities to handle multi-class data with high inter-class similarity or high intra-class variation. The kernel random coordinate descent (KRCD) algorithm is proposed for 1 minimization in the kernel space under the KSRC framework. It allows the proposed method to obtain satisfactory classification accuracy when inter-class similarity is high. The training samples are partitioned in multiple scales and rotated in different resolutions to create a generative model that is invariant to scale and rotation changes. This model enables the KSRC framework to overcome the high intra-class variation problem for scene categorization. The experimental results show the proposed method obtains more stable performances than other existing state-of-art scene categorization methods.

This paper presents a novel decision feedback equalizer (DFE) with block delay detection for the joint transceiver design that uses channel state information (CSI). The block delay detection in the proposed DFE offers a degree of freedom for optimizing the precoder of the transmitter, provided the transmission power is constrained. In the proposed DFE, the feedforward matrix is devised to enable a block-based equalizer that can be cooperated with an intrablock decision feedback equalizer for suppressing the intersymbol interference (ISI) for the transmitted block with a certain block delay. In this design, the interblock interference (IBI) for the delay block is eliminated in advance by applying the recently developed oblique projection framework to the implementation of the feedforward matrix. With knowledge of full CSI, the block delay and the associated block-based precoder are jointly designed such that the average bit-error-rate (BER) is minimized, subject to the transmission power constraint. Separate algorithms are derived for directly determining the BER-minimized block delays for intrablock minimum mean-squared error (MMSE) and zero-forcing (ZF) equalization criteria. Theoretical derivations indicate that the proposed MMSE design simultaneously maximize the Gaussian mutual information of a transceiver, even under the cases of existing IBI. Simulation results validate the proposed DFE for devising an optimum transceiver with CSI, and show the superior BER performance of the optimized transceiver using proposed DFE. Relying on analytic results and simulation cases also builds a sub-optimum MMSE design of the proposed DFE using the BER-minimized block delay for ZF criterion, which exhibits almost identical BER performance as the proposed MMSE design in most of the signal-to-noise ratio (SNR) range.

This letter proposes a monopole multi-sector antenna with dielectric cylinder, and shows some results of simulations that examined the antenna characteristics. The dependency of radiation characteristics on relative permittivity εr shows the lens effect with increase of εr. Furthermore, the characteristics of the proposed antenna are improved by optimizing the termination conditions at the quiescent antennas. The backlobe level is lower than -10 dB. Also, the vertical HPBW and the conical HPBW are around 70.5° and 63.4°, respectively. The optimization improved the actual gain by 2 dB. It is found that the diameter of the proposed antenna is 1/3rd that of the conventional one.

The design and measured results of a 120-GHz transmitter and receiver chipset are described in this paper. A simple on-off keying (OOK) modulation is adopted for low power consumption. The proposed transmitter and receiver are fabricated using 65-nm CMOS technology. The current consumption of the transmitter and receiver are 19.2 mA and 48.2 mA respectively. A 9-Gbps PRBS is successfully transferred from the transmitter to the receiver with the bit error rate less than 10-9.

This letter proposes an automatic IQ imbalance compensation technique for quadrature modulators by means of spectrum measurement of RF signal using a spectrum analyzer. The analyzer feeds back only magnitude information of the frequency spectrum of the signal. To realize IQ imbalance compensation, the conventional method of steepest descent is modified; the descent direction is empirically determined and a variable step-size is introduced for accelerating convergence. The experimental results for a four-channel transmitter operating at 11 GHz are presented for verification.

We are interested in retrieving video shots or videos containing particular people from a video dataset. Owing to the large variations in pose, illumination conditions, occlusions, hairstyles and facial expressions, face tracks have recently been researched in the fields of face recognition, face retrieval and name labeling from videos. However, when the number of face tracks is very large, conventional methods, which match all or some pairs of faces in face tracks, will not be effective. Therefore, in this paper, an efficient method for finding a given person from a video dataset is presented. In our study, in according to performing research on face tracks in a single video, we also consider how to organize all the faces in videos in a dataset and how to improve the search quality in the query process. Different videos may include the same person; thus, the management of individuals in different videos will be useful for their retrieval. The proposed method includes the following three points. (i) Face tracks of the same person appearing for a period in each video are first connected on the basis of scene information with a time constriction, then all the people in one video are organized by a proposed hierarchical clustering method. (ii) After obtaining the organizational structure of all the people in one video, the people are organized into an upper layer by affinity propagation. (iii) Finally, in the process of querying, a remeasuring method based on the index structure of videos is performed to improve the retrieval accuracy. We also build a video dataset that contains six types of videos: films, TV shows, educational videos, interviews, press conferences and domestic activities. The formation of face tracks in the six types of videos is first researched, then experiments are performed on this video dataset containing more than 1 million faces and 218,786 face tracks. The results show that the proposed approach has high search quality and a short search time.

This letter considers a dual-hop multiuser MIMO amplify-and-forward relay broadcast system with multi-antenna nodes. A unified scheme is addressed to jointly optimize the linear transceiver based on the sum mean-square error (MSE) and the sum rate criterion. The solutions are iteratively obtained by deriving the gradients of the objective functions for a gradient descent algorithm. Simulation results demonstrate the performance improvements in terms of the BER and the sum rate.