nils-herrmann/clean_scirepeval huggingface dataset:
A robust H.264 video streaming scheme for portable devices

We propose a novel error resilient video coding and streaming scheme specially designed for the streaming of H.264 coded video to portable devices in this work. The scheme is based on the error feedback and tracking techniques, and it utilizes the SP/SI coding method introduced in H.264. During the video streaming process, the sender identifies macroblocks that have been affected by previous errors based on the feedback information from the receiver. Then, it re-encodes these macroblocks into secondary SP macroblocks with predictions from concealed reference frames and uses them to replace the originally coded version in the bit stream. As proven by experimental results, the scheme is capable of stopping or reducing the error propagation effect caused by transmission errors. It demands a small bit rate overhead if there is a transmission error, and no bit rate overhead, otherwise. Experimental results are provided to demonstrate the error resilient performance of the proposed scheme.
Improved H.264/AVC Lossless Intra Coding With Two-Layered Residual Coding (TRC)

A lossless image coding method, known as the two-layered residual coding (TRC) scheme, is proposed in this letter. After the H.264/AVC lossy intra prediction, we propose an advanced scheme for residual coding, which consists of two residual coders in cascade. The first-layer residual coder is conducted via transform and quantization with a coarser quantization parameter. The second-layer residual coder is a bit-plane coding method. It is shown experimentally that the TRC scheme outperforms the H.264/AVC lossless intra coding with an averaged bit rate saving of about 24%.
Rate Control for H.264 Video With Enhanced Rate and Distortion Models

A new rate control scheme for H.264 video encoding with enhanced rate and distortion models is proposed in this work. Compared with existing H.264 rate control schemes, our scheme has offered several new features. First, the inter-dependency between rate-distortion optimization (RDO) and rate control in H.264 is resolved via quantization parameter estimation and update. Second, since the bits of the header information may occupy a larger portion of the total bit budget, which is especially true when being coded at low bit rates, a rate model for the header information is developed to estimate header bits more accurately. The number of header bits is modeled as a function of the number of nonzero motion vector (MV) elements and the number of MVs. Third, a new source rate model and a distortion model are proposed. For this purpose, coded 4 times 4 blocks are identified and the number of source bits and distortion are modeled as functions of the quantization stepsize and the complexity of coded 4 times 4 blocks. Finally, a R-D optimized bit allocation scheme among macroblocks (MBs) is proposed to improve picture quality. Built upon the above ideas, a rate control algorithm is developed for the H.264 baseline-profile encoder under the constant bit rate constraint. It is shown by experimental results that the new algorithm can control bit rates accurately with the R-D performance significantly better than that of the rate control algorithm implemented in the H.264 software encoder JM8.1a
Layered video multicast with ECN over Differentiated Service networks

A layered video multicast framework for differentiated service (DS) networks, which provides various levels of QoS guarantee for heterogeneous users, is examined in this research. The proposed system consists of three key components: extended active queue management, hierarchical priority marking, and receiver-driven layered multicast with ECN (RLME). Particularly, we introduce RLME that effectively utilizes advanced features of active queues such as random early drop (RED) and early congestion notification (ECN) in DS networks. The usage of ECN combined with the early response to congestion of RLME reduces actual packet losses significantly, and the priority support from DS networks minimizes the packet loss effect on video quality. The network performance and video quality from simulation results show that the proposed system successfully achieves stable and controllable video QoS guarantee for heterogeneous video clients.
Design of a memory-scalable wavelet-based image codec

The goal of this research is to develop a high performance image codec to be implemented in a digital signal processor (DSP). This DSP chip has only a small amount of internal memory that is fast enough to keep up with the clock cycle of CPU. A new wavelet image codec called the scalable binary description (S-BiD) codec is proposed to achieve this goal. S-BiD, consists of an external wavelet transform and the block-based quantization scheme. The external wavelet algorithm uses a DWT-specific pre-fetching technique to reduce the impact of large access delay of a bulk storage device. Wavelet coefficients are quantized into a set of interleaved multiple bit-streams that describe the three layers in the quantization hierarchy, i.e. blocks, subbands and coefficients, respectively. The codec can generate good compressed images even when the size of the cache memory is less than 4 Kbyte. With a cache memory of 16 Kbyte, its PSNR performance is comparable with all other codecs while its coding time is the shortest. If more resources are available, its performance will be even better.
Energy allocation for multicarrier systems with mixed QoS classes

An energy allocation method for multicarrier systems that allows effective transmission of mixed source data with varying quality of service (QoS) requirements is presented. We consider different types and different classes of data that are simultaneously transmitted over non-uniform channels. The two commonly considered data types are multimedia and alpha-numeric data. Within the multimedia data type, there are audio, video and graphic data classes. The addition of multiple classes necessitates that the bit ordering across carriers is optimized. In addition to the bit ordering rule, we extend this concept and define a parameter called the QoS scaling factor. Through manipulation of the QoS scaling factor, the allocation of distortion in a multiclass multicarrier environment is controllable. Our algorithm performs optimal energy allocation among carriers and enables the system to meet the performance targets for all classes of data. Theoretical bounds are presented, and performance of the algorithm is illustrated by numerical simulation under varying conditions.
A Generic Scheme for Progressive Point Cloud Coding

In this paper, we propose a generic point cloud encoder that provides a unified framework for compressing different attributes of point samples corresponding to 3D objects with an arbitrary topology. In the proposed scheme, the coding process is led by an iterative octree cell subdivision of the object space. At each level of subdivision, the positions of point samples are approximated by the geometry centers of all tree-front cells, whereas normals and colors are approximated by their statistical average within each of the tree-front cells. With this framework, we employ attribute-dependent encoding techniques to exploit the different characteristics of various attributes. All of these have led to a significant improvement in the rate-distortion (R-D) performance and a computational advantage over the state of the art. Furthermore, given sufficient levels of octree expansion, normal space partitioning, and resolution of color quantization, the proposed point cloud encoder can be potentially used for lossless coding of 3D point clouds.
V-BLAST Receiver and Performance In MIMO Relay Networks with Imperfect CSI

Previous work demonstrated that the improvements in spectral efficiency and link reliability can be obtained in wireless relay networks employing terminals with MIMO capability. In order to take the advantage of MIMO relay networks while mitigate the complexity of decoding procedure, we propose a scheme that applies ZF relaying at the relay terminals and utilizes MMSE V-BLAST receiver at the destination terminal for two- hop half-duplex coherent MIMO relay networks. Considering the channel estimation is often imperfect due to the noise and interference, this paper extends the V-BLAST receiver design to the imperfect channel state information (CSI), assuming the channel estimation errors are independent complex Gaussian with zero mean and known second-order statistics. A robust MMSE nulling operator and its corresponding symbol detection ordering criterion is proposed for the MMSE V-BLAST receiver, which aims at providing, in each layer, the minimum average mean square error (MSE), over the random channel errors. The proposed ordering rule achieves global average MSE optimization which results in better performance than the previously proposed robust ZF V-BLAST. It has been shown that the proposed design exploits the characteristics of MIMO relay networks to provide good performance with respect to imperfect CSI while keeping a low complexity of the decoding procedure.
Optimized opportunistic multicast scheduling (OMS) over heterogeneous cellular networks

Optimized opportunistic multicast scheduling (OMS) has been studied previously by the authors for homogeneous cellular networks, where the problem of efficiently transmitting a common set of data from a single base station to multiple users that have identical channel statistics was examined. It has been demonstrated that OMS can achieve significant performance improvement by exploiting the optimal tradeoff between multiuser diversity and multicast gain. In this work, we extend our studies to heterogeneous networks with users subject to different channel statistics. Specifically, we consider a single cell wireless network with users uniformly distributed in a circular region around the base station. Since users with low SNR are the ones that hinder system throughput, we argue that system performance may be predicted by the behavior of users in the outmost ring of the cell, which are approximately homogeneous. Using extreme value theory and results obtained from the homogeneous case, we determine the optimal user selection ratio for a homogeneous ring of users near the edge of the cell and then use it to derive the optimal selection ratio over the entire heterogeneous network. Simulations confirm theoretical results and illustrate the effectiveness of the proposed scheme.
Run-time power consumption modeling for embedded multimedia systems

The run-time power consumption model for multimedia application routines in an embedded system is developed in this paper. A wide range of benchmarks for these routines such as image, video and speech coding algorithms are examined extensively to characterize their power consumption behavior. Then, based on this study, a run-time power consumption model is proposed to achieve fast and accurate power usage estimation, where the model depends on the specific application routine involved as well as the applied voltage and the operating frequency. It is demonstrated that the developed model is able to predict the cumulative energy consumption of validating sequences with little error. Finally, this model is validated with a commercial VLIW processor by checking its actual power consumption behavior.
View-Dependent Visibility Estimation for Tree Models

A view-dependent visibility estimation technique for tree models is proposed in this work. While most previous work focused on visibility estimation of large objects in architectural walkthroughs, we consider the visibility estimation problem of tree leaves in complex natural scenes such as forests. Exact calculation of how each leaf object blocks another from a given viewpoint is difficult due to the large amount of computational cost. To address this issue, we propose three simple yet effective methods for efficient visibility estimation of tree leaves: the distance-based, the normal-based, and the layer-plus-normal-based methods. Experimental results show that the distance-based method always produces the best analytical performance, the normal-based method works better in preserving volumetric visual quality at low budget constraints, and the layer-plus-normal-based method preserves volumetric visual quality while yielding excellent analytical performance.
Simplified Multiaccess Interference Reduction for MC-CDMA With Carrier Frequency Offsets

Multicarrier code-division multiple-access (MC-CDMA) system performance can severely be degraded by multiaccess interference (MAI) due to the carrier frequency offset (CFO). We argue that MAI can more easily be reduced by employing complex carrier interferometry (CI) codes. We consider the scenario with spread gain N, multipath length L, and N users, i.e., a fully loaded system. It is proved that, when CI codes are used, each user only needs to combat 2(L - 1) (rather than N - 1) interferers, even in the presence of CFO. It is shown that this property of MC-CDMA with CI codes in a CFO channel can be exploited to simplify three multiuser detectors, namely, parallel interference cancellation (PIC), maximum-likelihood, and decorrelating multiuser detectors. The bit-error probability (BEP) for MC-CDMA with binary phase-shift keying (BPSK) modulation and single-stage PIC and an upper bound for the minimum error probability are derived. Finally, simulation results are given to corroborate theoretical results.
Hybrid Data and Decision Fusion Techniques for Model-Based Data Gathering in Wireless Sensor Networks

The data gathering problem in wireless sensor networks for environmental monitoring, where the physical phenomena can be modeled by partial differential equations (PDE's), is investigated. Under this context, it suffices for the sensor network to update the base station with estimates of model parameters rather than transmitting raw sensor measurements. In-network processing techniques to estimate the PDE coefficients are presented. A scheme that provides a hybrid combination of decision and data fusion is proposed to find a tradeoff between performance and energy efficiency. The role that the assumptions of PDE models can play in designing such methods is investigated.
A region-based H.263+ codec and its rate control for low VBR video

This paper presents a region-based video codec, which is compatible with the H.263+ standard, and its associated rate control algorithm for low variable-bit-rate (VBR) video. The proposed region-based coding scheme is a hybrid method that incorporates traditional block DCT coding as well as object-based coding. To achieve this, we adopt H.263+ as the platform, and develop a fast macroblock-based segmentation method to implement the new region-based codec. The associated rate control solution includes rate control in three levels: encoding frame selection, frame-layer rate control and macroblock-layer rate control. The goal is to improve human visual perceptual quality at low bit rates. The efficiency of the proposed rate control algorithm applied to the region-based H.263+ codec is demonstrated via several typical test sequences.
Reducing memory bank conflict for embedded multimedia systems

Memory bank conflict is an important issue to be addressed to enhance the performance of embedded multimedia systems. This paper presents an analysis of the memory bank conflict problem. Based on the analysis, a novel scheme utilizing single instruction multiple data (SIMD) and array padding technique is introduced to reduce the memory bank conflict phenomenon. Since the array padding distance has a great impact on the overall conflict reduction, we propose a model-based confliction estimation scheme and a probabilistic model to determine the optimal padding distance. Experimental results are given to demonstrate the effectiveness of the proposed scheme
Identification of speakers in movie dialogs using audiovisual cues

The problem of identifying speakers from a movie dialog scene is addressed in this paper. While most previous work on speaker identification has been carried out using pure audio data, more robust results could be obtained by integrating the knowledge from multiple media sources such as visual and audio information when they are available. In this work, we first identify and isolate speech segments from background by applying video shot detection, audio classification and adaptive silence detection techniques, then a decision is made based on the calculated likelihood between the incoming speech data and pre-trained speaker/background models. Moreover, to verify the effectiveness of the adaptive silence detector, we have compared it with a statistically trained silence model. Experimental results show that the proposed algorithm can achieve approximately 84% identification accuracy by integrating multiple media cues.
Optimized Opportunistic Multicast Scheduling over Cellular Networks

The design of optimal opportunistic multicast scheduling (OMS) that maximizes the throughput of cellular networks is investigated. In a cellular network, the base station (BS) transmits the same information to multiple users within a cell. Recently, Gopala et al. proposed a median-user static OMS scheme in which a BS selects and broadcasts to the best 50% users in each transmission until all users are served. This scheduling scheme has been shown to exploit both the multiuser diversity and the multicasting gain simultaneously. In this work, we examine the optimal user selection ratio in each transmission. Based on extreme value theory, we first derive the limiting distribution of the maximum decodable rate of the M-th best user and the corresponding average number of transmissions required to serve all users. Then, the optimal selection ratio is established by maximizing the average network throughput. Furthermore, a dynamic selection algorithm is proposed to adjust the user selection ratio adaptively in each transmission. It is shown by simulation results that the OMS scheme with optimized static and dynamic selected ratios outperform the conventional unicast, multicast and the median-user static OMS schemes.
Regional Bit Allocation and Rate Distortion Optimization for Multiview Depth Video Coding With View Synthesis Distortion Model

In this paper, we propose a view synthesis distortion model (VSDM) that establishes the relationship between depth distortion and view synthesis distortion for the regions with different characteristics: color texture area corresponding depth (CTAD) region and color smooth area corresponding depth (CSAD), respectively. With this VSDM, we propose regional bit allocation (RBA) and rate distortion optimization (RDO) algorithms for multiview depth video coding (MDVC) by allocating more bits on CTAD for rendering quality and fewer bits on CSAD for compression efficiency. Experimental results show that the proposed VSDM based RBA and RDO can improve the coding efficiency significantly for the test sequences. In addition, for the proposed overall MDVC algorithm that integrates VSDM based RBA and RDO, it achieves 9.99% and 14.51% bit rate reduction on average for the high and low bit rate, respectively. It can improve virtual view image quality 0.22 and 0.24 dB on average at the high and low bit rate, respectively, when compared with the original joint multiview video coding model. The RD performance comparisons using five different metrics also validate the effectiveness of the proposed overall algorithm. In addition, the proposed algorithms can be applied to both INTRA and INTER frames.
Buffer-constrained R-D optimized rate control for video coding

Buffer-constrained R-D optimized rate control for video coding is investigated in this work. A frame level bit allocation is first presented based on a model of the relationship between the rate (R) and nonzero (NZ) coefficients. With the modelled R-NZ relationship, a quality feedback scheme is proposed to generate VBV (video buffer verifier) compliant bitstream with assured video quality. Then, a R-D optimized macroblock level rate control is described by jointly selecting the quantization parameter and the coding mode of macroblocks in I, B and P pictures for both progressive and interlaced video. To avoid the irregularly large MV or one single isolated coefficient, we extend the set of coding modes of MB by including zero MV and zero texture bits as two more candidates. Finally, fast heuristics are developed to reduce the computational complexity of R-D data generation and the Viterbi algorithm (VA) in R-D optimization, which achieves coding results close to the optimal one at a much lower computational cost.
Performance of asynchronous long-code multicarrier CDMA systems in the presence of frequency offsets and correlated fading

The effects of frequency offsets and aperiodic random spreading sequences on the performance of asynchronous multicarrier code division multiple access (CDMA) systems with correlated fading are investigated in this research. Random parameters including asynchronous delays, correlated Rayleigh fading and spreading sequences are averaged to determine the covariance matrix of the interference-plus-noise vector. An analytic expression for the average signal-to-interference-plus-noise ratio (SINR) is obtained. Furthermore, average bit error probability (BEP) based on the Gaussian approximation is also derived. We show that the system degrades significantly if the frequency offset of the desired user is present, while the system is insensitive to interferers' frequency offsets. In consequence, it is crucial to estimate and compensate the desired user's synchronization imperfection. Finally, design tradeoff among the number of subcarriers, fading correlations, and inter-carrier interference (ICI) are presented in simulation results.
An embedded DCT approach to progressive image compression

Motivated by Shapiro's (see  1993) embedded zerotree wavelet coding (EZW) and Taubman and Zakhor's (see , p.572-88, 1994) layered zero coding (LZC), we propose a layered DCT image compression scheme, which generates an embedded bit stream for DCT coefficients according to their importance. The new method allows progressive image transmission and simplifies the rate-control problem. In addition to these functionalities, it provides a substantial rate-distortion improvement over the JPEG standard when the bit rates become low. For example, we observe a bit rate reduction with respect to the JPEG Huffman and arithmetic coders by about 60% and 20%, respectively, for a bit rate around 0.1 bpp.
Rate Control Optimization for Temporal-Layer Scalable Video Coding

A novel frame-level rate control (RC) algorithm is presented in this paper for temporal scalability of scalable video coding. First, by introducing a linear quality dependency model, the quality dependency between a coding frame and its references is investigated for the hierarchical B-picture prediction structure. Second, linear rate-quantization (R-Q) and distortion-quantization (D-Q) models are introduced based on different characteristics of temporal layers. Third, according to the proposed quality dependency model and R-Q and D-Q models for each temporal layer, adaptive weighting factors are derived to allocate bits efficiently among temporal layers. Experimental results on not only traditional quarter common intermediate format/common intermediate format but also standard definition and high definition sequences demonstrate that the proposed algorithm achieves excellent coding efficiency as compared to other benchmark RC schemes.