nils-herrmann/clean_scirepeval huggingface dataset:
Video over IEEE802.11 wireless LAN: A brief survey

With relatively high transmission capacity and usually unconstrained connections, IEEE802.11 WLANs provide the ideal infrastructure for pervasive video content sharing and communications. However, the delivery of high-performance video streams over 802.11 WLANs remains a challenging task due to the inherent characteristics of compressed video and dynamic channels. In this paper, we present a brief survey of various recent innovations that have been developed to enhance the Quality of Service (QoS) performance for video over WLANs. Based on the application scenarios, the solutions have focused mainly on three network layers, that is, Application layer (APP), Media Access Control layer (MAC), and Physical layer (PHY). After reviewing the video compression technology, we first examine various single-layer solutions for video over WLANs. We then discuss several cross-layer solutions that take advantage of mutual interactions between different network layers. Finally, several technical issues beyond QoS performance, including energy and security, are also addressed. We conclude that the application of video over WLANs will continue to increase in future.
A Novel Authentication Scheme Based on Acceleration Data in WBAN

Node authentication is essential in wireless body area network (WBAN), as the data collected in the WBAN is important and closely related to the personal privacy especially in the health applications. Traditional authentication solutions usually require priori knowledge, advanced hardware or out-of-band channels, which are impractical for the WBAN, and the data-based authentication scheme has been proved to be a promising solution. In this paper, we propose a novel authentication scheme which uses acceleration information collected in the WBAN to determine whether a node is legal. The solution is achieved by exploiting the similarity in the acceleration data between the legal node and the node under authentication. Compared to other data-based authentication schemes, the proposed scheme is more practical, more accurate and with lower false positive rate (FPR).
Buffer-Aware Resource Allocation Scheme With Energy Efficiency and QoS Effectiveness in Wireless Body Area Networks

Wireless body area network (WBAN) has attracted more and more attention to automatically and intelligently sense the health data of one person for supporting various health applications in smart cities. In the energy-constrained and heterogeneous WBAN system, there are three main issues: 1) the dynamic link characteristics due to the time-varying postures and environments; 2) the high energy efficiency requirement with considering the limited sensor battery; and 3) the high quality-of-service (QoS) requirement due to the importance of health data. To provide long service with high quality, the resource allocation scheme becomes indispensable with considering all these issues. In this paper, a mix-cost parameter is designed to evaluate the energy efficiency and QoS effectiveness, and a resource allocation problem is formulated to minimize the total mix-cost with optimizing the transmission rate, the transmission power, and the allocated time slots for each sensor. Then, a buffer-aware sensor evaluation method with low complexity is introduced to the resource allocation scheme to evaluate the sensor state in real time and then decide when applying for the resource re-allocation by the hub for further improving both the short-term and the long-term QoS performance. Finally, a greedy sub-optimal resource allocation scheme is designed to reduce the time complexity of the resource allocation scheme. Simulation results are presented to demonstrate the effectiveness of the proposed optimal buffer-aware resource allocation scheme as well as the greedy sub-optimal resource allocation scheme with low complexity.
JSM-2 based ECG compression with statistical support prediction

This paper addresses the problem of developing an efficient compression scheme with high quality and low computational complexity for ECG signal compression. Taking into account the joint sparsity existing in ECG data and the temporal dependencies in ECG signal sequence, a novel scheme for JSM-2 based ECG compression is developed to exploit these characteristics. We first predict support information in sparse domain from the previous ECG data for the current recovery process. Then a modified Simultaneous Orthogonal Matching Pursuit Algorithm (SOMP) algorithm is proposed to incorporate the idea of support information establishment for JSM-2 based ECG compression. Simulation results show that the proposed JSM-2 based ECG compression scheme with statistical support prediction outperforms existing schemes with enhanced performance and low computational complexity.
Multiresolution block sampling-based method for texture synthesis

We present an efficient multiresolution block sampling-based texture synthesis algorithm that works well for a wide variety of challenging textures. We consider the texture synthesis as a procedure that first estimates and then resamples a probability function. To achieve the effect of good and fast estimation of the probability function for a given texture as well as to retain the structural information during synthesis, we propose a concept of block sampling and a corresponding novel scheme of texture synthesis based on multiresolution block sampling (MBS). The computational complexity of the proposed algorithm is much lower than that of existing algorithms. Experimental results have shown that his novel texture synthesis algorithm produces superior results for many challenging textures.
Cloud Mobile Media: Reflections and Outlook

This paper surveys the emerging paradigm of cloud mobile media. We start with two alternative perspectives for cloud mobile media networks: an end-to-end view and a layered view. Summaries of existing research in this area are organized according to the layered service framework: i) cloud resource management and control in infrastructure-as-a-service (IaaS), ii) cloud-based media services in platform-as-a-service (PaaS), and iii) novel cloud-based systems and applications in software-as-a-service (SaaS). We further substantiate our proposed design principles for cloud-based mobile media using a concrete case study: a cloud-centric media platform (CCMP) developed at Nanyang Technological University. Finally, this paper concludes with an outlook of open research problems for realizing the vision of cloud-based mobile media.
Texture-assisted Kinect depth inpainting

The emergence of Kinect facilitates the possibility of depth capture in real-time and with low cost by consumers. It also provides powerful tool and inspiration for researchers to engage in new array of technology development. However, the quality of the depth map captured from Kinect is still inadequate for many applications due to holes, noises and artifacts existing within the depth information. In this paper, we present a texture assisted Kinect depth inpainting framework, aiming at obtaining improved depth information. In this framework, the relationship between texture and depth is investigated, and the characteristics of depth are also exploited. More specifically, texture edge information is extracted to assist the depth inpainting. Furthermore, filtering and diffusion are designed for hole-filling and edge alignment. Experiment results demonstrate that the Kinect depth can be appropriately repaired in both smooth and edge region. Comparing with the original depth, the inpainted depth information enhances the quality of advanced processing such as 3D reconstruction.
A New Color-Based Lane Detection Via Gaussian Radial Basis Function Networks

Lane detection plays a central role in intelligent transportation systems. While edge detection on intensity images has gained much popularity in the past, it usually results in noisy binary images. Most noticeably, the color information of the scene that may provide an important cue for lane detection has not been genuinely considered. In this paper, we propose a novel color-based lane detection system. Although color-based schemes have their fair share of issues, including varying illumination conditions, by relying on a lane mark color predictor obtained from an offline supervised training of Gaussian radial basis function (GRBF) networks, such issues can be appropriately overcome. Experimental results have demonstrated that the proposed approach, in contrast to predominantly edge-based approaches, can effectively eliminate erroneous edges that do not belong to the lane marks in well-structured scenes.
A Transform Domain Classification Based Wyner-Ziv Video Codec

In theory, a Wyner-Ziv video codec should achieve the same efficiency as a joint encoding and decoding one. However, existing approaches still exhibit significant gaps. One main reason is the lack of the complete correlation exploitation between source and side information. In this paper, we propose a transform domain classification based Wyner-Ziv video codec, aiming at exploiting additional video statistics. In this proposed new scheme, the encoder exploits additional statistics by performing block classification to differentiate low motion blocks from high motion ones. In general, low motion blocks represent highly correlated regions. Such information is useful when the decoder performs motion-compensated interpolation to obtain better side information, thus improving the performance of Wyner-Ziv coding. Experimental results show that we are indeed able to achieve better rate-distortion performance compared to the existing Wyner-Ziv video codecs at the expense of some additional complexity in frame store and comparisons at the encoder.
TCP-Oriented Raptor Coding for High-Frame-Rate Video Transmission Over Wireless Networks

High-frame-rate (HFR) video technology is becoming widely implemented in popular multimedia applications (e.g., Youtube and cloud gaming) to provide a smooth viewing experience, while transmission control protocol (TCP) is pervasively adopted as the transport-layer solution for video communications to achieve firewall traversal and network friendliness. However, it is severely challenging to effectively deliver real-time HFR video over TCP: 1) HFR video streaming features high transmission rate, enhanced frame density, and stringent delay constraint and 2) the packet retransmission and congestion control mechanisms in TCP may cause frequent throughput fluctuations and deadline violations. Motivated by addressing these critical issues, this research presents an application-layer forward error correction (FEC) framework dubbed Raptor coded HFR video over TCP (ROCHET). First, we develop a mathematical model to analyze the frame-level distortion of systematic Raptor code-based HFR video communication over TCP in wireless networks. Second, we propose a joint approximate distortion estimation and Raptor coding adaption solution to minimize the sum of total distortion. The proposed ROCHET is able to effectively leverage unequal error protection and TCP state analysis to enhance streaming video quality. We conduct the performance evaluation through extensive emulations in Exata involving real-time HFR video encoded with H.264 codec. Compared with the existing FEC coding schemes, ROCHET achieves appreciable improvements in terms of video peak signal-to-noise ratio, goodput, and frame success rate. Thus, ROCHET is recommended for TCP-based HFR video transmission over wireless networks.
Face location in wavelet-based video compression for high perceptual quality videoconferencing

We present a human face location technique based on contour extraction within the framework of a wavelet-based video compression scheme for videoconferencing applications. In addition to an adaptive quantization in which spatial constraints are enforced to preserve perceptually important information at low bit rates, semantic information of the human face is incorporated to design a hybrid compression scheme for videoconferencing since the human face is often the most important portion within a frame and should be coded with high fidelity. The human face is detected based on contour extraction and feature point analysis. An approximated face mask is then used in the quantization of the decomposed subbands. At the same total bit rate, coarser quantization of the background enables the face region to be quantized finer and coded with higher quality. Simulation results have shown that the perceptual image quality can be greatly improved using the proposed scheme.
Impact of ATM traffic control on MPEG-2 video quality

In this paper, a performance study of controlled MPEG-2 video traffic over an ATM network is presented. ATM networks are able to support variable bit rate (VBR) video sources. However, to implement QoS contract enforcement, traffic policers such as a Leaky Bucket (LB) need to be incorporated in order to change the VBR characteristics of a video stream. Our study investigates the video quality achievable by different traffic policing mechanisms. We use cell loss, frame corruption, and mean square error (MSE) to evaluate the influence of different traffic policers on the quality of the transmitted video stream. The performance evaluation is accomplished by simulating an ATM network using real MPEG-2 video streams. In our study, we also consider the layered video coding offered by the MPEG-2 standard. With traffic control, layered video achieves significant quality improvement for video transmission over ATM as compared to the one-layer case.
Towards viewing quality optimized video adaptation

For video delivery over heterogeneous networks, the bandwidth mismatch at the receiver edge often leads to inevitable degradation of video quality during adaptation. While most studies in this field are based on maximizing PSNR (peak-signal-to-noise-ratio), many psychophysical experiments discover that viewing quality is not correlated well with PSNR but significantly influenced by the viewing conditions (e.g. display size and viewing distance), which are determined by the receiver device. In this research, we show that major picture quality evaluation schemes are not suitable for subjective quality driven video adaptation because they are unable to track the correspondence between viewing condition and viewing quality. In this paper we investigate a novel paradigm that performs adaptation with respect to the target display scenario in order to maximize the viewing quality. We demonstrate that viewing ratio (VR) plays a key role in linking viewing conditions and perceptual quality of given video signals. We convert the linkage between VR and perceptual quality into a computationally feasible algorithm for video adaptation. Experimental results show the VR based video adaptation scheme not only outperforms the benchmarks in terms of quality-of-experience for designated viewing scenarios, but also provides generally an improved visual quality for mobile devices with bandwidth constraint.
New Depth Coding Techniques With Utilization of Corresponding Video

With the development of 3D display and interactive multimedia systems, new 3D video applications, such as 3DTV and Free Viewpoint Video, are attracting significant interests. In order to enable these new applications, new data formats including captured 2D video sequences and corresponding depth maps have been proposed. Compared to conventional video frames, depth maps have very different characteristics. First, they typically consist of homogeneous areas partitioned by sharp edges representing depth discontinuities, while the sharp discontinuities play very important roles in view rendering. Second, there exists structure similarity between depth map and corresponding video, in which the edges in depth exhibit quite similar behaviors as the edges in the corresponding video. In conventional video coding techniques with transforms followed by quantization, there usually exist large artifacts along sharp edges and it costs significant more bits to represent the edges with higher accuracy. In order to suppress the coding artifacts while preserving edges, and to better compress depth information, we propose in this paper two new depth compression techniques: Trilateral Filter and Sparse Dyadic Mode. Both techniques utilize the structure similarity between depth and corresponding video while focusing on different aspects in depth compression. As a new in-loop filter, Trilateral Filter is designed to filter depth with coding artifacts based on the proximity of pixel positions, the similarity among depth samples, as well as the similarity among the collocated pixels in the video frame. While Sparse Dyadic Mode is used as an intra mode to reconstruct depth map with sparse representations of depth blocks and effective reference of edge information from video frames. With these two new coding tools, we can achieve up to about 1.5 dB gain on rendering quality as compared to depth sequences coded using MVC under the same coding rate.
Service provisioning and profit maximization in network-assisted adaptive HTTP streaming

Mobile adaptive HTTP streaming with centralized consideration of multiple streams has gained increasing interest. It poses a special challenge that the interests of both content provider and network operator need to be deliberately balanced. More importantly, the adaptation is required to be flexible enough to be ported to various systems that work under different network environments, QoE levels, and economic objectives. To address these challenges, we propose a Markov Decision Process (MDP) based network-assisted adaptation framework, wherein cost of buffering, significant playback variation, bandwidth management and income of playback are jointly investigated. We then demonstrate its promising service provisioning and maximal profit for a mobile network in which fair or differentiated service is required.
Distributed video coding with zero motion skip and efficient DCT coefficient encoding

In this paper, we propose a suite of efficient schemes for the representation of spatial and temporal correlations of video signals in distributed video coding (DVC). These schemes consist of zero motion skipping, Gray codes, and sign bits coding of DCT coefficients developed to improve the overall rate-distortion (R-D) performance of distributed video coding. Existing schemes have focused on exploiting the spatial and temporal correlation without sufficient investigation on the efficient representation of the correlation. We believe this is one of the reasons that there still exists substantial gap between current DVC and traditional hybrid video coding. In traditional hybrid coding, a suite of efficient representation schemes such as zig-zag scan, run length code, and skipped macroblock have contributed significantly to excellent R-D performance. The efficient representation schemes we developed for DVC in this research will also lead to improved rate-distortion performance comparing with existing DVC schemes. We present in this paper the overall framework for the proposed zero motion skip and the analysis for efficient representations of both DCT coefficients and their signs. The experiment results show that the distributed video coding based on these efficient representations is able to achieve considerably improved rate-distortion performance over existing schemes.
Irregular Repetition Slotted ALOHA with Priority (P-IRSA)

In this paper, a random access with priority protocol named irregular repetition slotted ALOHA with priority (PIRSA) is introduced. By optimizing the packets repetition and using successive interference cancellation (SIC), irregular repetition slotted ALOHA (IRSA) has achieved a high throughput. Contention resolution diversity slotted ALOHA with access control (AC-CDRSA) enhances both throughput and efficiency under high traffic load. In P-IRSA, priority is considered in order to handle traffics from the users who demands enhanced access and throughput. Access control is added before the traffic, and users with high priority gain higher probability to access the channel under high traffic load. Further more, performance of the proposed P- IRSA in terms of the packet loss rate, throughput and channel efficiency are verified by simulations and are compared with IRSA and AC-CDRSA protocols. Simulation results show that the throughput of users with high priority can be enhanced under high traffic load with the proposed protocol.
Performance evaluation of H.264 video over ad hoc networks based on dual mode IEEE 802.11B/G and EDCA MAC architecture

We present in this paper the performance evaluation for H.264/AVC video transmission over wireless ad hoc networks. In order to achieve robust video transmission under ad hoc mode, the proposed system not only develops a physical rate based strategy for dual band IEEE 802.11 b/g, but also adopts EDCA MAC layer architecture of IEEE 802.1 le for an improved QoS performance. The dual mode operation allows the ad hoc terminals to move within a larger coverage area while maintaining robust connection via 802.1 lb/g. The adopted EDCA MAC layer architecture enables the prioritized transmission of differentiated video traffic for various ad hoc terminals. We have also developed several network level metrics, including bit rate, packets delay and drop rate, to evaluate the proposed scheme in comparison with simple dual band IEEE 802.11b/g. Simulation results demonstrate that the proposed EDCA-based scheme is able to outperform the simple dual band IEEE 802.1 lb/g with much improved received video quality.
Syndrome-Based Light-Weight Video Coding for Mobile Wireless Application

In conventional video coding, the complexity of an encoder is generally much higher than that of a decoder because of operations such as motion estimation consume significant computational resources. Such codec architecture is suitable for downlink transmission model of broadcast. However, in the contemporary applications of mobile wireless video uplink transmission, it is desirable to have low complexity video encoder to meet the resource limitations on the mobile devices. Recent advances in distributed video source coding provide potential reverse in computational complexity for encoder and decoder. In the same spirit, we proposed in this paper a syndrome-based light-weight video encoding scheme for mobile wireless applications. This scheme is based on two innovations: (1) adoption of low resolution low quality reference frames for motion estimation at the decoder; (2) introduction of more powerful product accumulate code. Extensive experimental results have confirmed that this syndrome based encoding can reduce computational complexity at the encoder while maintaining good reconstruction quality at the decoder. Therefore, this light weight video coding scheme is suitable for mobile wireless applications
A collusion resilient key management scheme for multi-dimensional scalable media access control

This paper proposes a novel key management scheme for multi-dimensional scalable multimedia access control. We build up a collusion-attack model and prove that the proposed scheme is indeed resilient to collusion attack. The lower bound of number of the segment keys is also given in the analysis. We consider the key management problem on partially order set and propose a general approach consists of a poset decomposition step and an element projection step. Under the proposed framework, a novel hierarchical 3D poset decomposition approach is further developed. The proposed scheme is the first provable collusion resilient scheme in 3-dimension (and higher) scenario. It can be easily adapted to other scalable dependence structure and higher dimension. Analysis on the proposed scheme proves its collusion-resilient property.