nils-herrmann/clean_scirepeval huggingface dataset:
MCL-JCV: A JND-based H.264/AVC video quality assessment dataset

A compressed video quality assessment dataset based on the just noticeable difference (JND) model, called MCL-JCV, is recently constructed and released. In this work, we explain its design objectives, selected video content and subject test procedures. Then, we conduct statistical analysis on collected JND data. We compute the difference between every two adjacent JND points and propose an outlier detection algorithm to remove unreliable data. We also show that each JND difference group can be well approximated by a normal distribution so that we can adopt the Gaussian mixture model (GMM) to characterize the distribution of multiple JND points. Finally, it is demonstrated by experimental results that the proposed JND analysis performed in the difference domain, called the D-method, achieves a lower BIC (Bayesian information criteria) value than the previously proposed G-method.
EVQA: An ensemble-learning-based video quality assessment index

A full-reference video quality assessment (VQA) method, called the ensemble-learning-based video quality assessment (EVQA) index, is proposed in this work. As compared with previous learning-based VQA methods, it has two unique features. First, EVQA adopts a frame-based learning mechanism to address the limited training data problem. Second, a dynamic image quality assessment(IQA) fusion scheme is developed by taking three factors into account: the spatial complexity and temporal context of a frame in a video source and the strength of IQA indices. In the test stage, EVQA applies the derived IQA fusion rule to different frames and take an average of the frame-based scores to generate the final video quality score. The superior performance of the proposed EVQA index is demonstrated by experimental results conducted on both LIVE and MCL-V video databases.
Perceptual image compression with wavelet transform

A perceptual image compression method by using the wavelet transform is proposed in this work. This method differs from conventional wavelet coding schemes by incorporating Human Visual System (HVS) characteristics in the quantization stage. Instead of encoding amplitudes of wavelet coefficients directly, we investigate the coding of contrasts of each resolution. The resulting compression scheme is able to distribute visual errors uniformly over the whole image. Thus, the visual artifact at low bit rate is minimized. Experimental results are given to show the superior visual performance of the new method in comparison with those of the conventional wavelet coders.
Reliable wireless video transmission via fading channel estimation and adaptation

The quality of video transmitted over time-varying wireless channels relies heavily on the coordinated effort to cope with both channel and source variations dynamically. Given the priority of each source packet and the estimated channel condition, an adaptive protection scheme based on joint source-channel criteria is investigated via proactive forward error correction (FEC). With proactive FEC in Reed Solomon (RS)/rate-compatible punctured convolutional (RCPC) codes, we study a practical algorithm to match the relative priority of source packets and instantaneous channel conditions. The channel condition is estimated to capture the long-term fading effect in terms of the averaged SNR over a preset window. Proactive protection is performed for each packet based on the joint source-channel criteria with special attention to the accuracy, time-scale match, and feedback delay of channel status estimation. The overall gain of the proposed protection mechanism is demonstrated in terms of the end-to-end wireless video performance.
Enlarged Block Sizes and Motion Search Ranges for High Definition Video Coding

A rate-distortion (R-D) model is derived to investigate the potential coding gain from the use of a larger macroblock size for high definition (HD) video coding in this work. Coding rates of using different block sizes for HD video coding are compared with the R-D model, and limitations of the current coding techniques that might impede the additional R-D gain of using enlarged MB for HD coding are explained. Experiments show that an average bit rate gain of 27 % across QP range can be achieved by using enlarged MB and extended motion search range.
Design of optimal FIR prefilters for wavelet coefficient computation

M.J. Shensa previously proposed an algorithm in the computation of wavelet series transform (WST) or continuous wavelet transform (CWT), where a sampled signal is first prefiltered. The Mallat's discrete wavelet transform (DWT) algorithm is then applied to the prefiltered sequence. The prefiltering is used to reduce the approximation error between the computed and desired wavelet transform coefficients. The optimal finite impulse response (FIR) prefilter design problem for the Shensa algorithm in computing the WST coefficients is studied. It is shown numerically that the error for the computed WST coefficients is reduced significantly more by using the designed optimal prefilters than that obtained from the algorithm of S. Mallat.<<ETX>>
Motion compensated video compression and dense motion field coding

A new method based on an efficient computational algorithm and a novel coding scheme is proposed for the design and implementation of an integrated video compression system. The proposed system offers better performance and more functionality over the state of the art encoding method, i.e. the MPEG. Multiple bit rate decoding, low bit rate encoding, and scalability of the method to very high resolution video are among some of the advantages offered by the proposed system.<<ETX>>
Robust video frame rate up-conversion (FRUC) techniques

Two challenging situations for video frame rate up-conversion (FRUC) are first identified; namely, when the input video has abrupt illumination change and/or a low frame rate. Then, a low-complexity robust FRUC algorithm is proposed to address these two issues. The proposed algorithm employs a translational motion vector (MV) model of the first- and the second- order and detects the continuity of these motion vectors (MVs). The superior performance of the proposed algorithm has been tested extensively and representative examples are given in this work.
Distributed parameter estimation for monitoring diffusion phenomena using physical models

In this work, we address the problem of estimating parameters of diffusion phenomena via autonomous wireless sensor networks. Diffusion phenomena, such as the propagation of a gas in the air or of a chemical agent in the water, can be modeled by means of partial differential equations (PDE's). In several scenarios, the parameters characterizing such models, i.e. the coefficients of the PDE's, are not known a-priori and need to be estimated. We develop an adaptive approach for the distributed identification of the parameters of diffusion models for both the cases of known and unknown boundary conditions (BCs). The technique also applies to the case of spatially varying parameters. We present simulation results to show the performance and the various trade-offs of the method.
TCP-friendly Internet video streaming employing variable frame-rate encoding and interpolation

A feedback-based Internet video transmission scheme based on ITU-T H.263+ is presented. The proposed system is capable of continually accommodating its stream size and managing the packet loss recovery in response to network condition changes. It consists of multiple components: TCP-friendly end-to-end congestion control and available bandwidth estimation, encoding frame-rate control and delay-based smoothing at the sender, media-aware packetization and packet loss recovery tied with congestion control, and quality recovery tools such as motion-compensated frame interpolation at the receiver. These components are designed to meet the low computational complexity requirement so that the whole system can operate in real-time. Among these, the video-aware congestion control known as a receiver-based congestion control mechanism, the variable frame-rate H.263+ encoding, and fast motion-compensated frame interpolation components are key features. Through a seamless integration, it is demonstrated that network adaptivity is enhanced enough to mitigate the packet loss and bandwidth fluctuation, resulting in a more smooth video experience at the receiver.
Moving cast shadow elimination for robust vehicle extraction based on 2D joint vehicle/shadow models

A new algorithm to eliminate moving cast shadow for robust vehicle detection and extraction in a vision-based highway monitoring system is investigated. The proposed algorithm is based on a simplified 2D vehicle/shadow model of six types projected on to a 2D image plane. Parameters of the joint 2D vehicle/shadow models can be estimated from the input video without light source and camera calibration information. Simulations are performed to verify that the proposed technique is effective for vision-based highway surveillance systems.
Design and performance evaluation of TCP-friendly thin-layered video multicast scheme

The design of a TCP-friendly layered video multicast scheme with thin layer partitioning is studied in this research. It was shown in Nahm et al. (2003) that the cumulative layered multicast with static layers can achieve TCP-friendly network adaptation with good fairness via the usage of thin layers. However, if the layer is thinner than the scale of network fluctuation, the convergence to the target throughput may not be attainable even in the steady state. In this work, we propose a simple nonlinear preprocessing, called the minmax averaging operation, in the basic loss rate estimation algorithm, to help a TCP-friendly throughput estimation robust to network fluctuation. It is demonstrated via computer simulation that the stability of the network adaptation performance has been improved with the usage of the proposed scheme.
A Change-Point Detection Approach to Power Quality Monitoring in Smart Grids

In this work, we apply a change-point detection approach to power quality (PQ) monitoring in smart grids. Capitalizing on change-point detection theory with unknown parameters, a sequential cumulative sum (CUSUM)-based scheme is developed with an objective to provide quick and accurate detection of PQ event occurrence in real time. The proposed CUSUM-based scheme evaluates the weighted likelihood ratios by exploiting both the instantaneous and the long-term information of the power waveform. It is shown by computer simulations that the proposed CUSUM-based scheme can achieve a significant performance gain over conventional detection schemes.
Complexity reduction of joint temporal-spatial bit allocation using R-D models for video streaming

The joint temporal-spatial bit allocation problem was examined in our previous work to achieve proper temporal-spatial quality tradeoff for low bit rate video coding. Both theoretical analysis and performance benchmark of several optimal/suboptimal algorithms were presented. However, the high computational complexities of these solutions prevent them from being used in practical applications. To solve this problem, rate-distortion (R-D) models are adopted in this work to reduce the complexity of the proposed rate control scheme. Different R-D models are applied to intra, inter and skipped frames, respectively, with consideration of both prediction and interpolation dependencies among successive frames. A look ahead window (LAW) structure is implemented, with buffer and delay constraints applied, for continuous and smooth video playback. The approximation errors of the proposed R-D models are very small, which results in small degradation of the compressed video quality, while the complexity of rate control is greatly reduced so that it is suitable for streaming applications. It is shown by experiments that the proposed rate control method can achieve better overall quality than the standard MPEG-4/TM7 rate control.
Disparity Estimation and Virtual View Synthesis from Stereo Video

A new scheme for disparity vector (DV) estimation and virtual view synthesis to generate 3D video display from a pair of stereo video inputs is investigated in this work. Two performance metrics are considered for the algorithmic evaluation; i.e. quality and complexity. To enhance the overall performance, a two-stage algorithm for accurate and fast DV estimation and occlusion handling is first presented. Then, a preprocessing algorithm and a synthesis method are described. The proposed preprocessing algorithm can remove false matched regions for DV refinement effectively. The new synthesis method can reduce blurring and ghostly effects greatly. It is demonstrated by experimental results that the proposed algorithm offers better virtual view quality at a much lower complexity than existing methods.
Mobile Multiuser Access with Approximately MAI-free PMU-OFDM Transceiver Design

A new multiuser OFDM transceiver with precoding was introduced by Tsai, Lin and Kuo in . The system can reduce multiaccess interference (MAI) due to the carrier frequency offset (CFO) to a negligible amount by the use of even or odd Hadamard-Walsh codewords. The performance of this system in a mobile environment, where the channel response varies within one OFDM symbol due to the Doppler effect, is evaluated in this work. It is shown that the use of even or odd Hadamard-Walsh codewords can greatly reduce the MAI due to the Doppler effect as well. It is also demonstrated by simulations that all Hadamard-Walsh codes except for the all-one code result in considerable suppression of ICI due to the Doppler effect. Finally, we show that the new system with odd Hadamard-Walsh codes outperforms a half-loaded OFDMA system in a mobile channel environment.
Adaptive Multi-path Prediction for Error Resilient H.264 Coding

An adaptive reference selection (ARS) scheme is proposed to enhance error resilience performance of H.264 video in this work, where multiple prediction paths can be created in the compressed video stream at the macroblock level without a large amount of bit rate overhead. We first develop a method to measure the expected distortion at the decoder when the H.264 video is transmitted through erroneous channels. Then, we use an updated rate-distortion cost function to incorporate this measurement into the mode decision process. The best prediction for each macroblock is selected with the objective to achieve the highest expected rate-distortion performance of the GOP in the received video stream. It is shown by experimental results that error propagation is largely reduced and the quality of received video stream is improved significantly by the proposed scheme
Joint temporal-spatial bit allocation for video coding with dependency

The joint temporal-spatial bit allocation problem with consideration of dependency arising from motion compensated prediction as well as frame interpolation is investigated in this research. After the problem formulation, several heuristic methods are proposed to provide near-optimal and suboptimal solutions to this problem. First, the selective iteration algorithm (SIA) based on the monotonic property of the rate-distortion (R-D) curve is proposed to achieve the near-optimal solution. Then, the greedy iteration algorithm (GIA) is presented as a suboptimal heuristic to reach an R-D performance close to that obtained using SIA, while at a much lower complexity. Furthermore, by adaptively grouping frames based on the mean of the absolute difference differentials and applying greedy pruning to groups of frames, the suboptimal solution is significantly expedited so that it can be applied in real-time applications. Frames to be skipped in the coding process and quantization parameters (QPs) exploited in coded frames are adaptively and jointly determined to reach a proper tradeoff between temporal and spatial qualities. Experimental results show that the proposed methods can enhance the overall quality of compressed video at various bit rates in comparison with H.263+/TMN8 using fixed frame rates and QPs, as well as the adaptive quantization solution proposed in.
A Simplified Rate Control Scheme for Non-Conversational H.264 Video

In this work, a simplified rate control algorithm is proposed for non-conversational H.264 video applications. When a GOP (group of pictures) structure is imposed on an encoded video, a bit rate control and a bit allocation among frames are two important components of a rate control algorithm. We employ a GOP rate model and the monotonicity property to address the bit rate control and the frame-layer bit allocation problem, respectively. Since the proposed algorithm employs only a GOP rate model, the rate control mechanism can be greatly simplified while it achieves better video quality as compared with that in the H.264 JM8.6 reference encoder.
Single nucleotide polymorphism data analysis - State-of-the-art review on this emerging field from a signal processing viewpoint

The basic structural units of the genome are nucleotides. A single nucleotide polymorphism (SNP) is a mutation at a single nucleotide position. This paper discusses several major problems in SNP data analysis and review some existing solutions in this work. Generally speaking, a rich set of SNP analysis problems are cast in the signal processing framework. Our objective is to offer a state-of-the art review on this topic from a signal processing viewpoint so that researchers in the signal processing field can grasp the important domain knowledge to overcome the barrier between the two fields
View-dependent transmission of 3-D normal meshes

A view-dependent three-dimensional (3-D) normal mesh transmission technique is proposed in this work. A normal mesh is first partitioned into several segments, which are compressed independently. Each segment is given a different priority according to its visibility from the client's viewing position, which is sent to the server through a feedback channel. With the visibility criterion, the compressed bitstream of each segment is optimally truncated using a Lagrangian multiplier method. Moreover, when the viewing position of the client changes, the visibility priority of each segment is updated in the server and additional mesh information is transmitted to the client accordingly. Simulation results show that the proposed technique can reduce the transmission bandwidth significantly while maintaining the same visual quality.
Security and privacy in online social networks: A survey

Social networking becomes increasingly important due to the recent surge in online interaction. Social network analysis can be used to study the functioning of computer networks, information flow patterns in communities, and emergent behavior of physical and biological systems. In this paper, the mathematical formulation and computational models for security and privacy of social network data are discussed. Several possible ways for an attacker to attack are presented so that the mathematical formulation can take them into account. The metrics for measuring the amount of security and privacy in an online social network (OSN) are discussed so that we have an idea of how good a model is. Based on these current techniques and attack strategies, future directions of research are discussed.
Progressive coding of 3-D graphic models

Based on state-of-the-art graphic-simplification techniques and progressive image-coding schemes, we propose a new hierarchical three-dimensional graphic-compression scheme in this research. This scheme progressively compresses an arbitrary polygonal mesh into a single bitstream. Along the encoding process, every output bit contributes to the reduction of coding distortion, and the contribution of bits decreases according to their order of position in the bitstream. At the receiver end, the decoder can stop at any point while giving a reconstruction of the original model with the best rate-distortion tradeoff. A series of models of continuous varying resolution can thus be constructed from the single bitstream. This property, which is referred to as the embedding property since the coding of a coarser model is embedded in the coding of a finer model, can be widely used in robust error control, progressive transmission and display, level-of-detail control, etc. It is demonstrated by experiments that an acceptable quality level can be achieved at a compression ratio of 20 to 1 for several test graphic models.
Robust video segmentation employing variable bandwidth object boundary

A pixel-wise accurate and interactive video segmentation technique is proposed in this paper to generate a binary mask of moving objects optimized for MPEG-4 object-based video coding. The initial object mask is tracked temporally, and regions are classified into the background region, the object region, and the uncertain region where the pixel is within a certain distance from the tracked object boundary. We exploit the color feature in the L*u*v* space, and use a non-parametric gradient-based iterative color clustering algorithm, known as the mean shift algorithm, to generate the region marker in the background and the object regions. Furthermore, we use the watershed technique to classify pixels in the uncertain region into the background and the object. Finally, by employing a variable bandwidth region boundary, the final mask for moving objects is optimized for MPEG-4 shape coding efficiency. The shape coding efficiency can be improved up to 30% with negligible loss of perceptual quality.
A progressive algorithm for perceptual coding of digital audio signals

In this paper, a progressive audio coding algorithm is presented. Distinctive from existing transform-based perceptual audio coding schemes, which allow either constant bit rate or multiple fixed bit rates, our proposed algorithm achieves a fully embedded audio coding scheme whose bit rate can be controlled depending on the user's requirement. This feature makes it extremely useful in audio networking applications, such as audio on-demand and audio broadcasting over the Internet. In the proposed audio coding scheme, efficient successive quantization and bit layer coding are applied to the compact audio signal representation obtained from traditional subband decomposition. Our research focuses on the improved successive approximation quantisation (ISAQ), which performs bit allocation for quantization based on psychoacoustic analysis of the input audio signal. Thus the progressive audio coding is achieved, while perceptually transparent audio coding is also maintained to the allowance of bit rate constraint. The performance measurement of our presented algorithm is demonstrated.
A sliding window approach to real-time H.263+ frame rate adjustment

H.263+ is an emerging video compression standard for the low bit rate visual communication. Up to now, most H.263+ rate control algorithms, especially that in the test model of the near-term (TMN), focus on macroblock level bit allocation and low latency under a constant-frame-rate and constant-bit-rate (CBR) channel. As expected, these algorithms are not capable of handling the transmission bandwidth fluctuation and the video quality can be degraded seriously. We propose a new H.263+ rate control scheme which supports the variable bit rate (VBR) channel through the frame rate adjustment. In particular, a fast realization of encoding frame rate control based on motion information within the sliding window is developed to efficiently pursue the tradeoff between spatial/temporal qualities. Experimental results are provided to demonstrate the superior performance of the proposed scheme.