nils-herrmann/clean_scirepeval huggingface dataset:
Structure-sensitive superpixels via geodesic distance

Over-segments (i.e. superpixels) have been commonly used as supporting regions for feature vectors and primitives to reduce computational complexity in various image analysis tasks. In this paper, we describe a structuresensitive over-segmentation technique by exploiting Lloyd's algorithm with a geodesic distance. It generates smaller superpixels to achieve lower under-segmentation in structure-dense regions with high intensity or color variation, and produces larger segments to increase computational efficiency in structure-sparse regions with homogeneous appearance. We adopt geometric flows to compute the geodesic distances amongst pixels, and in the segmentation procedure, the density of over-segments is automatically adjusted according to an energy functional that embeds color homogeneity, structure density and compactness constraints. Comparative experiments with the Berkeley database show that the proposed algorithm outperforms prior arts while offering a comparable computational efficiency with fast methods, such as TurboPixels.
Collaborative Quantization for Cross-Modal Similarity Search

Cross-modal similarity search is a problem about designing a search system supporting querying across content modalities, e.g., using an image to search for texts or using a text to search for images. This paper presents a compact coding solution for efficient search, with a focus on the quantization approach which has already shown the superior performance over the hashing solutions in the single-modal similarity search. We propose a cross-modal quantization approach, which is among the early attempts to introduce quantization into cross-modal search. The major contribution lies in jointly learning the quantizers for both modalities through aligning the quantized representations for each pair of image and text belonging to a document. In addition, our approach simultaneously learns the common space for both modalities in which quantization is conducted to enable efficient and effective search using the Euclidean distance computed in the common space with fast distance table lookup. Experimental results compared with several competitive algorithms over three benchmark datasets demonstrate that the proposed approach achieves the state-of-the-art performance.
Design of Automatic Lock Devices Based on the MCP2515 CAN-Bus

A control system based on the CAN-bus is designed to meet the real-time, reliable performance of the automatic lock devices. Modularization design idea is adopted. The control system consists of the main control module, the station of extracting the key teeth coding, the station of loading up billiards, down billiards, spring, the station of detecting lock, the station of sealing. Each station has a common, integrated MCP2515 CAN-bus controller circuit board. It makes the functional module be a CAN node in the CAN network, and the modules exchange data by CAN network. The result of the control system running indicated that it could meet the high speed requirement, reliable control, and easy maintainability.
Maximum Margin Clustering with Pairwise Constraints

Maximum margin clustering (MMC), which extends the theory of support vector machine to unsupervised learning, has been attracting considerable attention recently. The existing approaches mainly focus on reducing the computational complexity of MMC. The accuracy of these methods, however, has not always been guaranteed. In this paper, we propose to incorporate additional side-information, which is in the form of pairwise constraints, into MMC to further improve its performance. A set of pairwise loss functions are introduced into the clustering objective function which effectively penalize the violation of the given constraints. We show that the resulting optimization problem can be easily solved via constrained concave-convex procedure (CCCP). Moreover, for constrained multi-class MMC, we present an efficient cutting-plane algorithm to solve the sub-problem in each iteration of CCCP. The experiments demonstrate that the pairwise constrained MMC algorithms considerably outperform the unconstrained MMC algorithms and two other clustering algorithms that exploit the same type of side-information.
Content-dependent feature selection for block-based image steganalysis

Block-based image steganalysis, which conducts steganalysis on smaller homogenous blocks of a given test image, was proposed to improve the performance of steganalysis. However, the computational complexity of block-based image steganalysis is high when the feature size is large. To reduce the complexity, we develop a content-dependent feature selection scheme for a binary classifier. The main idea is to select important features depending on block types, which explains the term of “content-dependent” selection. This choice enables us to obtain better performance with a smaller number of features and reduce computational complexity at the same time. Experimental results are conducted to demonstrate the performance improvement of content-dependent feature selection with high detection accuracy.
Efficient Light-Field Rendering Using Depth Maps for 100-Mpixel Multi-Projection 3D Display

In order to achieve an immersive, natural 3D experience on a large screen, a 100-Mpixel multi-projection 3D display was developed. Ninety-six projectors were used to increase the number of rays emanating from each pixel in the horizontal direction to 96. Conventional algorithms use a large number of cameras or input images to process a large number of light rays. This creates difficulties in the design of both the large acquiring system and substantial memory storage. In this paper, we propose an efficient light-field rendering algorithm that utilizes only a few input colors and depth images. Using a depth map and estimated camera parameters, synthesized light-field images are directly generated. This algorithm requires a much lighter memory load than conventional light-field rendering algorithms. It is also much simpler than the image-based rendering algorithm because it does not require the generation of so many multiview images.
Joint symbol detection and channel estimation for MC-CDMA systems in the presence of carrier frequency offset

The problem of carrier frequency offset in multicarrier code-division multiple-access (MC-CDMA) systems is studied in this research. We present an iterative approach based on the expectation-maximization (EM) algorithm to estimate system parameters, including the channel state information, the carrier frequency offset and the interference-plus-noise covariance matrix. Furthermore, the symbol detection is jointly achieved through the evaluation of the Kullback-Leibler information measure required for the EM iteration. A closed form expression of the modified Fisher information matrix (MFIM) is derived to obtain the the modified Cramer-Rao bound (MCRB) of the vector version. Finally, we verity the effectiveness of the proposed algorithm with computer simulation.
Performance Comparison of Unstructured Content Discovery Techniques over Ad Hoc Networks

The performance of several unstructured peer-to- peer (P2P) content discovery techniques over ad hoc networks was analyzed in this work. They include: query flooding, expanding ring search, random walk and Bloom filter(BF)-based probabilistic routing. The chosen performance metrics are the query success rate, the route stretch and the search cost. Mathematic analysis is conducted to predict their behavior in static ad hoc networks. Finally, extensive computer simulations is performed to validate our analytical results in the ad hoc network. It is concluded that the BF-based probabilistic routing outperforms flooding-based and random walk schemes in finding a good balance among various performance metrics. Its only potential disadvantage is that the control packet size increases as the number of shared objects increases, which may not impose a severe constraint on a middle-sized ad hoc network.
On-line lossless mocap data compression

We investigate efficient on-line lossless coding of motion capture (mocap) data in this work. The mocap data consist of a set of curves as the temporal trajectory of variables known as the degrees of freedom (dofs). To achieve compression, we sample each dof's curve temporally, interpolate the curve by a piece-wise Hermite spline as the prediction, and encode residuals with DPCM and Huffman coding. We compare the fixed-interval and the adaptive-interval sampling methods. Both schemes can achieve an averaged bit rate saving of around 80% (or, equivalently, a compression ratio of 20%) with real-time encoding/decoding.
A Cross-Layer Approach to Contour Nodes Inference with Data Fusion in Wireless Sensor Networks

A cross-layer approach to contour nodes inference of monitored physical phenomena with data fusion in wireless sensor networks is investigated in this work. The authors first analyze three sources of signal distortion: sensing noise, data quantization error and data communication noise. The sensing noise is often negligible. We need to choose the proper data quantization levels to balance the communication cost and the desired signal quality. Besides, data fusion at a local fusion center can be used to mitigate the communication noise due to the poor wireless channel. Instead of making a hard binary decision, the probability for a sensor node to be a contour node is calculated at the local fusion center. An adaptive data fusion scheme is proposed to avoid excessive packet retransmissions. Simulation results are given to show the effects of different system parameters on the overall system performance.
Fractal estimation from noisy data via discrete fractional Gaussian noise (DFGN) and the Haar basis

The authors show that the application of the discrete wavelet transform (DWT) using the Haar basis to the increments of fractional Brownian motion (fBm), also known as discrete fractional Gaussian noise (DFGN), yields coefficients which are weakly correlated and have a variance that is exponentially related to scale. Similar results were derived by Flandrin (1989), Tewfik, and Kim for a continuous-time fBm going through a continuous wavelet transform (CWT). The new theoretical results justify an improvement to a fractal estimation algorithm recently proposed by Wornell and Oppenheim. The performance of the new algorithm is compared with that of Wornell and Oppenheim's (see  1992) algorithm in numerical simulation.
Joint channel estimation and multiuser detection for multipath fading channels in DS-CDMA

The problem of joint blind channel estimation and multiple access interference (MAI) suppression for an asynchronous code-division multiple-access (CDMA) system is studied. A low-complexity sliding-window scheme based on the expectation maximization (EM) algorithm is developed for joint blind maximum a posteriori probability (MAP) multi-user detection (MUD) and stochastic maximum likelihood (ML) channel estimation in a dispersive fading channel. With multi-stage soft interference cancellation, MAI can be efficiently suppressed. Together with an initial value prediction method for algorithm initialization at each window, the proposed scheme can track fading channels on the fly with no phase ambiguities even when channel gains are close to zero.
Reversible variable length codes (RVLC) for robust coding of 3D topological mesh data

In order to limit error propagation, we divide the topological data of the entire mesh into several segments. Each segment is identified by its synchronization word and header. Due to the use of the arithmetic coder, data of a whole segment would often become useless in the presence of even a single bit error. Furthermore, several adjacent segments may be corrupted simultaneously at high bit error rates (BER). As a result, a lot of data would be required to be retransmitted in the presence of errors. Retransmitted data may also in turn get corrupted in high BER conditions. This would result in a considerable loss of coding efficiency and increased delay. We propose the use of reversible variable length codes (RVLC) to solve this problem. RVLC not only prevents error propagation in one segment but also efficiently detects the distorted portion of the bitstream due to their capability of two-way decoding. This would allow the recovery of a large portion of data from a corrupted segment. The amount of retransmitted data can thus be drastically reduced. RVLC can be matched to various sources with different probability distributions by adjusting their suffix length, and have been found suitable for image and video coding. However, the application of RVLC to robust 3D mesh coding has not yet been studied. Our study of the suitability of RVLC for the topological data is presented in this research. Experiments have been carried to prove the efficiency of the proposed robust 3D graphic coding algorithm. To design an efficient pre-defined code table, a large set of 300 MPEG-4 selected 3D models have been used in our experiments. The use of predefined code tables would result in a significantly reduced computational complexity.
GOP-based Rate Control for H.264/SVC with Hierarchical B-pictures

A GOP-based rate control algorithm for hierarchical B-pictures in H.264/SVC is proposed in this work. The problem is firstly formulated as a bit allocation problem among different temporal layers. Due to the dependency of these layers, we propose a Q-selection tree solution framework. The monotonicity property is exploited to prune the Q-selection tree. Then, the rate-distortion (R-D) data is calculated at a selected set of leaf nodes in any admissible Q-selection tree. The R-D data of other leaf nodes are interpolated using the log-linearity property of a local R-D model. It is shown by experiments that the proposed algorithm achieves a significant coding gain improvement at different target bit rates.
Retrieval and progressive transmission of wavelet compressed images

We examine the use of state-of-the-art wavelet coding techniques for content-based image retrieval in this research. It is shown that wavelet features, including the wavelet packet decomposition tree and the number of significant wavelet coefficients in each subband, serve as good indicators of image contents. By adopting these wavelet coding features, images can be compressed and indexed simultaneously, thus decreasing the complexity of database management. This technique finds applications in hierarchical retrieval and browsing of the image database, and facilitates the progressive transmission of retrieved images. Experiments are performed to demonstrate the retrieval efficiency of our new method.
Tempo-based MTV-Style Home Video Authoring

Automatic authoring of MTV-style home video using visual and music tempo analysis is studied in this work. In the proposed system, the input home video is first segmented into shots by low level features such as the color histogram difference. Then, three types of tempo analysis are conducted; namely, music, global visual (the frame level) and local visual (the facial expression level) tempo analysis. For local visual tempo analysis, we propose a scheme to compute the facial tension from a sequence of facial appearance variation. Finally, the authoring methodology is presented, which consists of music and visual tempo matching to product MTV-style video. Experiments are conducted using baby home video with encouraging results obtained
Performance analysis of multistage BLUE/MMSE receivers for DS-CDMA in frequency selective fading channels

The multistage (MS) Wiener filter proposed in [J.S. Goldstein et al., Nov. 1998] is extended to meet the best linear unbiased estimator (BLUE) criterion in this research. The MS BLUE filter is shown to share the same structure of the MS minimum-mean squared error (MMSE)/minimum output energy (MOE) filter bank proposed in S. H. Wu et al.  2002] for multipath channels modulo a scaling matrix. The limiting performance and the relationship between the output SINRs of MS-BLUE, MS-MMSE and MS-MOE multiuser receivers in a multipath fading channel are derived and linked to the resultant bit rate error (BER). It is shown in our analysis the BERs and SINRs of the MMSE, MOE and BLUE receivers are, respectively in flat Rayleigh fading channels.
Quality-of-service mapping mechanism for packet video in differentiated services network

This paper presents a futuristic framework for quality-of-service (QoS) mapping between practically categorized packet video and relative differentiated service (DiffServ or DS) network employing unified priority index and adaptive packet forwarding mechanism under a given pricing model (e.g., DiffServ level differentiated price/packet). Video categorization is based on the relative priority index (RPI), which represents the relative preference per each packet in terms of loss and delay. We propose an adaptive packet forwarding mechanism for a DiffServ network to provide persistent service differentiation. Effective QoS mapping is then performed by mapping video packets onto different DiffServ levels based on RPI. To verify the efficiency of proposed strategy, the end-to-end performance is evaluated through an error resilient packet video transmission using ITU-T H.263+ codec over a simulated DiffServ network. Results show that the proposed QoS mapping mechanism can exploit the relative DiffServ advantage and result in the persistent service differentiation among DiffServ levels and the enhanced end-to-end video quality with the same pricing constraint.
Color matching techniques for video mosaic applications

Color matching techniques are proposed to merge two or more video inputs of smaller sizes into one single larger output video with a wider field of view for video mosaic applications. The main challenge is to remove the seam lines between image boundaries due to the different color tone of the inputs. In this paper, color differences between input images are first compensated using the polynomial-based contrast stretching technique. Then, a linear filtering technique is adopted to remove the seam lines. The algorithms are developed in both the pixel domain and the DCT (discrete cosine transform) domain. The second approach is attractive for its lower computational complexity. Experimental results demonstrate that the color-matching problem can be satisfactorily solved in the compressed domain even when the DCT blocks of original input images are not aligned and also for the images taken with camera movement as long as image registration is done in advance. The proposed approach is applicable for MPEG2 video.
Performance Enhancement of Channel-Phase Precoded Ultra-Wideband (CPP-UWB) Systems by Rake Receivers

We propose to use the Rake receiver to improve the system performance by collecting more signal power in an ultra-wideband (UWB) system precoded by the channel phase information, called the CPP-UWB system , in this work. The performance of the proposed system is determined by the selected channel taps and the corresponding combining schemes for those Rake fingers. Three combing schemes, Le., the maximum ratio combining (MRC), the minimized mean square error (MMSE) and the zero-forcing (ZF), are proposed. When the MRC scheme is applied to the Rake receiver with M fingers, M channel taps can be easily found to maximize the averaged signal power at the receiver output by exploiting the property of the channel- phase-precoded channel. It is shown by simulation results that the proposed scheme significantly outperforms the preceding system using one matched filter as proposed in .
Reduced-rank multistage receivers for DS-CDMA in frequency-selective fading channels

Multistage (MS) implementation of the minimum mean-square error (MMSE), minimum output energy (MOE), best linear unbiased estimation (BLUE), and maximum-likelihood (ML) filter banks (FBs) is developed based on the concept of the MS Wiener filtering (MSWF) introduced by Goldstein et al. These FBs are shown to share a common MS structure for interference suppression, modulo a distinctive scaling matrix at each filter's output. Based on this finding, a framework is proposed for joint channel estimation and multiuser detection (MUD) in frequency-selective fading channels. Adaptive reduced-rank equal gain combining (EGC) schemes for this family of FBs (MMSE, MOE, BLUE, and ML) are proposed for noncoherent blind MUD of direct-sequence code-division multiple-access systems, and contrasted with the maximal ratio combining counterparts that are also formed with the proposed common structure under the assumption of known channel-state information. The bit-error rate, steady-state output signal-to-interference plus noise ratio (SINR), and convergence of the output SINRs are investigated via computer simulation. Simulation results indicate that the output SINRs attain full-rank performance with much lower rank for a highly loaded system, and that the adaptive reduced-rank EGC BLUE/ML FBs outperform the EGC MMSE/MOE FBs, due to the unbiased nature of the implicit BLUE channel estimators employed in the EGC BLUE/ML schemes.
Compressed-Domain Video Retargeting

In this paper, we present a compressed-domain video retargeting solution that operates without compromising the resizing quality. Existing video retargeting methods operate in the spatial (or pixel) domain. Such a solution is not practical if it is implemented in mobile devices due to its large memory requirement. In the proposed solution, each component of the retargeting system is designed to exploit the low-level compressed domain features extracted from the coded bit stream. For example, motion information is obtained directly from motion vectors. An efficient column shape mesh deformation is employed to solve the difficulty of sophisticated quad-shape mesh deformation in the compressed domain. The proposed solution achieves comparable (or slightly better) visual quality performance as compared with several state-of-the-art pixel-domain retargeting methods at lower computational and memory costs, making content-aware video resizing both scalable and practical in real-world applications.
MPEG-4 video codec IP design with a configurable embedded processor

Design of the MPEG-4 video codec IP (intellectual property) module with a configurable embedded processor architecture for the system-on-chip (SoC) application is presented in this research. First, we perform platform independent software optimization, in which the algorithmic optimization is conducted to improve the software performance for a general-purpose processor (GPP). Then, we obtain further performance improvement with the instruction-level hardware optimization, which is tailored to a configurable embedded processor architecture. The software optimization can be used in any application while the optimized instructions for video processing can be used in other video compression standards such as MPEG-1/2 and H.26L. With the two-step optimization approach, a significant performance improvement is achieved with high flexibility. In our experiment, the speed of the MPEG-4 simple profile level 1 (SP/L1) encoder is improved by 71 times. The developed IP enables the SoC design for multimedia applications within a short development period.
Preconditioned iterative methods for solving Toeplitz-plus-Hankel systems

The use of preconditioned iterative methods to solve a system of equations with a Toeplitz-plus-Hankel coefficient matrix is studied. A preconditioner for Toeplitz-plus-Hankel matrices is proposed, and the spectral properties of preconditioned rational Toeplitz-plus-Hankel matrices are examined. It is shown that the eigenvalues of the preconditioned matrix are clustered around unity except a finite number of outliers depending on the orders of the rational generating functions, and the clustering radius is proportional to the magnitude of the last elements in Toeplitz and Hankel matrices. With the spectral regularities, an N*N rational Toeplitz-plus-Hankel system can be solved by preconditioned iterative methods with O(N log N) operations.<<ETX>>