nils-herrmann/clean_scirepeval huggingface dataset:
Complexity Modeling of Spatial and Temporal Compensations in H.264/AVC Decoding

H.264/advanced video coding (AVC) decoding complexity modeling and applications are examined in this paper. We focus on complex modeling of spatial and temporal compensations achieved by a rich set of inter and intra-prediction modes of H.264/AVC. We study the relationship between motion vectors (MV), frame sizes, and distributions of selected reference frames, which are highly related to cache management efficiency and, thus, the decoding complexity. An H.264/AVC encoder equipped with the complexity models can choose the best inter or intra-prediction mode and the best MV or intra-prediction direction while meeting the decoding complexity constraint of the target receiver platform. The proposed complexity models are accurate. The application of complexity models to the H.264/AVC decoding complexity reduction is demonstrated.
A fusion-based video quality assessment (fvqa) index

In this work, we study the visual quality of streaming video and propose a fusion-based video quality assessment (FVQA) index to predict its quality. In the first step, video sequences are grouped according to their content complexity to reduce content diversity within each group. Then, at the second step, several existing video quality assessment methods are fused to provide the final video quality score, where fusion coefficients are learned from training video samples in the same group. We demonstrate the superior performance of FVQA as compared with other video quality assessment methods using the MCL-V video quality database.
Hierarchical classification of audio data for archiving and retrieving

A hierarchical system for audio classification and retrieval based on audio content analysis is presented in this paper. The system consists of three stages. The first stage is called the coarse-level audio classification and segmentation, where audio recordings are classified and segmented into speech, music, several types of environmental sounds, and silence, based on morphological and statistical analysis of temporal curves of short-time features of audio signals. In the second stage, environmental sounds are further classified into finer classes such as applause, rain, bird sound, etc. This fine-level classification is based on time-frequency analysis of audio signals and use of the hidden Markov model (HMM) for classification. In the third stage, the query-by-example audio retrieval is implemented where similar sounds can be found according to an input sample audio. It is shown that the proposed system has achieved an accuracy higher than 90% for coarse-level audio classification. Examples of audio fine classification and audio retrieval are also provided.
Combined bit swap and power gain adaptation for error rate equalization in DMT systems

A new adaptation algorithm, to equalize the symbol error rates over all subchannels, is proposed, to overcome the slow time-varying noise environment existing in xDSL channels. The proposed algorithm combines the conventional bit swap algorithm with power gain adaptation. The overall transmission power before and after adjustment is kept the same. Simulation results demonstrate that the proposed algorithm has a faster convergence speed and a smaller dynamic range of the equalized noise variance than the bit swap algorithm.
Performance Analysis and Transceiver Design for Adaptive BIC-MIMO-OFDM Systems

The performance analysis and transceiver design of an adaptive bit-interleaved-coded multi-input multi-output orthogonal frequency division multiplexing (BIC-MIMO-OFDM) system without channel station information (CSI) in priori are investigated in this research. First, the noncoherent capacity of a MIMO-OFDM system with TV subcarriers, nt transmit antennas and nr receive antennas is analyzed. It is shown that the lower bound of noncoherent capacity in the high signal-to-noise ratio (SNR) region is asymptotically equal to n*(1 - n*L/N) log rho, where n* = min(nl,nr), L is the number of channel taps and rho is the SNR value. Then, an adaptive BIC-MIMO-OFDM system based on transmitter beamforming and variable-rate-variable-power (VRVP) QAM is proposed. The throughput of adaptive scheme can achieve the noncoherent capacity, however, the gap to the coherent capacity cannot be totally compensated due to the overhead of training. The effect of imperfect channel state information (CSI) feedback is studied. It is demonstrated by numerical simulation that the proposed BIC-MIMO-OFDM scheme has better performance than adaptive trellis coded modulation (TCM) when outdated channel estimation is used.
Complexity Modeling for Motion Compensation in H.264/AVC Decoder

A complexity model for motion compensation in the H.264/AVC decoder is proposed. This model considers a rich set of inter prediction modes allowed by H.264 as well as the relationship of motion vectors (MVs), which are related to cache miss performance. This model is verified by experimental results. Possible applications of the complexity model are also described. One application scenario is to integrate it in an H.264 encoder so that the encoder can estimate the decoding complexity and choose the best inter prediction mode to meet the complexity constraint of the target decoding platform.
A new initialization technique for generalized Lloyd iteration

The generalized Lloyd algorithm plays an important role in the design of vector quantizers (VQ) and in feature clustering for pattern recognition. In the VQ context, this algorithm provides a procedure to iteratively improve a codebook and results in a local minimum that minimizes the average distortion function. We propose an efficient method to obtain a good initial codebook that can accelerate the convergence of the generalized Lloyd algorithm and achieve a better local minimum as well.<<ETX>>
Fast video object segmentation using affine motion and gradient-based color clustering

Video object segmentation is an important component for object-based video coding schemes such as MPEG-4. A fast and robust video segmentation technique, which aims at efficient foreground and background separation via effective combination of motion and color segmentation modules is proposed in this work. First, a non-parametric gradient-based iterative color clustering algorithm called the mean shift algorithm is employed to provide a robust initial dominant color regions according to color similarity. With the dominant color information obtained from previous frames as an initial seed for the next frame, we can reduce the amount of computational time by 50%. Next, moving regions are identified by a motion detection method based on the frame intensity difference, which helps to circumvent the motion estimation complexity for the whole frame. Only moving regions are further merged or split according to the region-based affine motion model. Furthermore, sizes, colors, and motion information of homogeneous regions are tracked to increase temporal and spatial consistency of extracted objects. The proposed system is evaluated for several typical MPEG-4 test sequences, and it provides very consistent and accurate object boundaries throughout the entire test sequences.
Graph representation for joint channel estimation and symbol detection

A unified structure is proposed for joint channel tracking and symbol detection in multipath fading channels. Based on the expectation maximization (EM) algorithm, a group of recursive stochastic filters is derived for blind channel estimation, using the maximum likelihood and minimum mean squared error criteria. In conjunction with the BCJR algorithm, it is shown that the recursive procedure for joint channel estimation and maximum a posteriori symbol detection can be represented as a message-passing scheme on a factor graph. The graphical model not only provides a generalized implementation architecture for existing training-based schemes, it also greatly reduces the complexity of existing algorithms for blind channel tracking.
Robust video multicast with joint network coding and AL-FEC

Robust H.264/SVC video multicast with joint network coding (NC) and application-layer forward error correction (AL-FEC) is presented in this work. Unlike traditional AL-FEC that protects the video source only, the NC scheme provides another level of protection by allowing the mixing of transmitted packets in the intermediate nodes of the network. The joint NC/AL-FEC solution simplifies the construction and maintenance of multicast trees greatly, and enables efficient video delivery to heterogeneous receivers. It is shown by computer simulation that the proposed joint NC/AL-FEC scheme outperforms the traditional store-and-forward (S/F) network with AL-FEC only by a large margin.
Artifact reduction in low bit rate wavelet coding with robust nonlinear filtering

A postprocessing algorithm for compression artifact reduction in low-bit-rate wavelet coding is proposed in this work. We first formulate the artifact reduction problem as a robust estimation problem. Under this framework, the artifact-free image is obtained by minimizing a cost function that accounts for the smoothness constraint as well as image fidelity. Unlike the traditional approach that adopts gradient descent search for optimization, a set of nonlinear filters is used to calculate the approximate global minimum. The nonlinear filtering approach reduces the number of the objective function evaluation and increases the speed of convergence. It is shown by experimental results that the proposed approach can alleviate wavelet coding artifacts efficiently with a low computational cost.
FOR/SOR video coding with super macroblock and inter-frame stripe prediction

A first-order-residual/second-order-residual (FOR/SOR) based video coding algorithm that incorporates the super macroblock (SMB) and the inter-frame stripe prediction (ISP) technique is proposed for high definition (HD) video coding in this work. We first examine the limitation of the SMB in high-bit-rate coding, and show that a simple extension of the block-size is not sufficient to get a significant improvement in coding performance. Then, we introduce the FOR/SOR coding technique to resolve this issue. For the FOR coding, we apply a larger quantization stepize and motion-predictive coding to remove the temporal correlation. Then, for the SOR coding, we propose an efficient prediction method, called the inter-frame stripe prediction (ISP) technique, to remove the structured residuals after the FOR coding to achieve a higher coding gain. It is demonstrated by experimental results that the proposed FOR/SOR algorithm outperforms H.264/AVC by a significant margin; namely, about 21.57% in the bit rate saving or 1.09dB in the PSNR improvement.
A distributed approach to contour line extraction using sensor networks

An algorithm to extract contour lines using wireless sensor networks is proposed in this work. In con- trast with previous work on edge detection that is primarily concerned with the region of a certain phenomenon, contour lines offer more detailed information about the underlying phenomenon such as signal's amplitude, density and source location. A distributed algorithm to extract the contour lines information from local measurements is developed so that the phenomenon can be monitored in the basestation without demanding excessive raw data transmission. Sim- ulation results are provided to demonstrate the efficiency of the proposed algorithm. Furthermore, a thorough per- formance analysis is conducted to understand the effects of the sensor density and the background noise power on the performance of the system.
Efficient implementation of elliptic curve cryptography (ECC) on VLIW-micro-architecture media processor

Elliptic curve cryptography (ECC) serves as an excellent candidate for secure embedded multimedia applications due to its small key size and high security protection. With performance profiling, several major bottlenecks of the ECC implementation are identified, and some suitable integer multiplication schemes over the VLIW and SIMD architecture are proposed. In particular, FIR-based multiplication using the special FIR instruction provided by Trimedia TM1300 was studied. The performance improvement of proposed schemes is reported and discussed
Discretization and solution of elliptic PDEs-a digital signal processing approach

A digital signal processing (DSP) approach is used to study numerical methods for discretizing and solving linear elliptic partial differential equations (PDEs). Whereas conventional PDE analysis techniques rely on matrix analysis and on a space-domain point of view to study the performance of solution methods, the DSP approach described here relies on frequency-domain analysis and on multidimensional DSP techniques. Both discretization schemes and solution methods are discussed. In the area of discretization, mode-dependent finite-difference schemes for general second-order elliptic PDEs are examined, and are illustrated by considering the Poisson, Helmholtz, and convection-diffusion equations as examples. In the area of solution methods, the authors focus on methods applicable to self-adjoint positive definite elliptic PDEs. Both direct and iterative methods are discussed, including fast Poisson solvers, elementary and accelerated relaxation methods, multigrid methods, preconditioned conjugate gradient methods and domain-decomposition techniques. In addition to describing these methods in a DSP setting, an up-to-date survey of recent developments is also provided.
Priority Ordering Algorithm for Scalable Video Coding Transmission over Heterogeneous Network

Scalable video representation of the state-of-art scalable extension of the H.264/MPEG-4 AVC (SVC) and its combined 3d scalability feature offer an excellent solution to flexible video multicast over IP network. In order to relieve the impact of the severe bandwidth fluctuations and packet loss to the reconstructed quality in heterogeneous networks like the internet, a GOP-adaptive layer-based priority ordering algorithm for SVC is proposed in this paper. The method ordered the SVC bit stream according to the rate distortion contribution of different layer to the whole performance within a GOP, which makes the transmission more efficient and robust under the same bandwidth condition. Simulation results of different sequences are given to demonstrate that the proposed algorithms offer better performance in video quality as compared the default SVC ordering method and the SNR-based ordering method.
An Embedded Space-Time Coding (STC) Scheme for Broadcasting

An embedded space-time coding method is proposed for wireless multimedia broadcast with heterogeneous receivers. In the proposed system, a transmitter sends out multi-layer source signals by encoding different layers with different space-time codes. Then, a receiver can retrieve a different amount of information depending on the number of its antennas. The receiver with only one antenna can decode only the base layer information with a low complexity while the receiver with more antennas can retrieve more layers of information. We also investigate a differential design of the embedded space-time system, which is used when the channel state information (CSI) is unknown to the receiver. Both analytic and experimental results are provided to demonstrate the performance of the proposed system. Differential detection with Kalman filtering is also investigated to help improve performance
Performance of linear reduced-rank multistage receivers for DS-CDMA in frequency-selective fading channels

The performance of a set of linear reduced-rank multistage filter banks is studied in the context of multiuser detection for direct-sequence (DS) code-division multiple-access (CDMA) systems. The set of filter banks under consideration is comprised of the minimum mean-square error (MMSE), the minimum output energy (MOE), the best linear unbiased estimator (BLUE), and the maximum-likelihood (ML) detector. Based on a common framework for the multistage implementations of the aforementioned filter banks, the signal-to-interference plus noise ratios (SINRs) and bit-error rates (BERs) of these reduced-rank filter banks are studied for multipath Rayleigh-fading channels. A generic BER formula is provided for coherent detection and noncoherent differential detection schemes constructed under this common framework. Analysis shows that all of these performance measures are characterized by a kernel matrix K/sub mmse/ whose trace forms the output SINR of the MMSE filter bank. Through investigating the recursive structure of K/sub mmse/, the output SINRs are proven to be monotonically increasing with the number of stages and upper-bounded by a number equal to the paths of the desired user's channel. The condition for asymptotically achieving this upper bound is also provided, which leads to the notion of effective user capacity of linear reduced-rank multiuser detection as well as serves as a test for the existence of a BER floor for coherent detection. In addition, the channel mismatch due to differential detection is also shown to yield a BER floor for noncoherent detection. Based on this analysis, a simple yet effective rule for choosing the number of stages is provided for both coherent and noncoherent linear multistage multiuser detection.
A new distortion/content-dependent video quality index (DCVQI)

A new video quality index, called the distortion/content-dependent video quality index (DCVQI), is proposed in this paper. The distortion and content effects on video quality assessment are taken into account explicitly in the DCVQI. First, we classify distortions into two types (local and global distortions) with a distortion classification scheme. Then, for a given distortion type, we observe a linear relation model between the perceptual quality and SSIM for a given video clip, and the parameters of the linear model are determined by video contents. These parameters can be obtained through a machine learning process. It is shown by experimental results the proposed DCVQI offers a PLCC (Pearson Linear Correlation Coefficient) value of 0.869 when tested on the LIVE database, which outperforms all state-of-the-art video quality assessment methods, including MOVIE and STMAD.
A multiresolution approach for image morphing

A new multiresolution approach for image morphing is proposed in this research. By exploring the fact that the human visual system recognizes primarily global features of objects in a fast changing image sequence, we use mainly the low frequency information of images in morphing. Besides, we consider the morphing process in the wavelet domain rather than in the spatial domain and, as a consequence, both spatial and frequency characteristics of the initial and final images in a range of resolution scales can be effectively used. Experimental results of morphing of two face images are given 20 illustrate the performance of the proposed method.<<ETX>>
Genomic sequence analysis using gap sequences and pattern filtering

A new pattern filtering technique is developed to analyze the genomic sequence in this research based on gap sequences, in which the distance of the same symbol is recorded consecutively as a sequence of integers. Sequence alignment and similarity testing can be performed on a family of gap sequences over selected patterns. The gap sequence offers a new way for sequence structural analysis. The match between the gap sequences is considered as a frame match while a true match requires both frame and stuffing match. Simulation results show that the extension of gap match indicates the corresponding segment extension in the original genomic sequence. Thus, we are able to generalize the conventional alignment and scoring methods in a more adaptive way.
Fast motion vector search for overlapped block motion compensation (OBMC)

The overlapped block motion compensation (OBMC) scheme provides an effective way to reduce block artifacts in video coding, and is adopted as an optional mode in the H.263 standard. However the motion vector search complexity increases significantly due to the motion interdependency of OBMC. In this work, we present a new OBMC motion vector search algorithm which reduces the computational complexity while preserving the decoded video quality. Unlike other iterative algorithms previously developed, our proposed algorithm requires no iteration during the motion vector search process. Furthermore, a fast search algorithm is adopted to reduce the search complexity. It is demonstrated by extensive experimental results that the proposed algorithm reduces a substantial amount of complexity and achieves a similar PSNR result in comparison with the existing iterative methods.
Content-based movie analysis and indexing based on audiovisual cues

A content-based movie parsing and indexing approach is presented; it analyzes both audio and visual sources and accounts for their interrelations to extract high-level semantic cues. Specifically, the goal of this work is to extract meaningful movie events and assign them semantic labels for the purpose of content indexing. Three types of key events, namely, 2-speaker dialogs, multiple-speaker dialogs, and hybrid events, are considered. Moreover, speakers present in the detected movie dialogs are further identified based on the audio source parsing. The obtained audio and visual cues are then integrated to index the movie content. Our experiments have shown that an effective integration of the audio and visual sources can lead to a higher level of video content understanding, abstraction and indexing.
Codeword Length Optimization for CPPUWB Systems

The optimal codeword length that generates the maximum output signal to interference ratio (SIR) for the channel-phase-precoded ultra-wideband (CPPUWB) system proposed in Y.H. Chang et al. (2006) is studied in this work to mitigate the interference in high data rate transmission. As compared with the proposed MMSE receiver in Y.H. Chang et al. (2006), this code length optimization technique demands no additional training symbols, which sacrifices the actual data rate, and maintains a simple receiver structure. This optimization problem is highly nonlinear in nature, and a fast search algorithm is developed to speed up the optimization process. The signal to interference plus noise ratio (SINR) performance of the proposed scheme degrades slightly when the input SNR is low, and it will converge to the maximum SINR as the input SNR becomes large
Robust encoding of 3D mesh using data partitioning

A low overhead data partitioning scheme for robust coding of 3D meshes is investigated in this research. The proposed algorithm fully exploits the component information of the 3D mesh topology and achieves both higher coding efficiency and error resilience. It first divides the 3D mesh into individual self-closed components by using constructive seed traversal. All components are classified and clustered into certain groups based on the statistical information of the component size. Each group is further partitioned into several segments. Next, the resynchronization words and headers are designed to combine segments into one whole bitstream. Errors in each segment can be independently detected and treated. Experimentals show a low overhead of 14.5% compared with the original error-free coding technique for 300 MPEG-4 selected 3D graphic models.