MPEG Video Sequences Research Articles

Robust MPEG Watermarking in DWT Four Bands

In this paper, we generalize an idea in a recent paper that embeds a binary pattern in the form of a binary image in the wavelet domain for images. Our generalization includes all four bands (LL, LH, HL and HH) in the DWT for MPEG video sequences. We tested the proposed algorithm against twelve attacks. Embedding the watermark in lower frequencies is robust to one group of attacks, and embedding the watermark in higher frequencies is robust to another group of attacks.

QoS assessment of 3G video-phone calls by tracing watermarking exploiting the new colour space ‘YST’

Tracing watermarking has been recently proposed as a technique to provide a blind measure of the quality of service of the communication link, focusing on multimedia communication scenarios. 3G communication scenarios, where each customer transmits both voice and MPEG-4 video sequences in real time, have been considered. Typical video-phone call consists of close shots of speakers, framing their face in the foreground. For such particular application, a novel colour space (YST) is adopted to minimise the perceptual distortions on face coding introduced by watermarking. In the YST space, the luminance component (Y) is the same as in conventional YUV space, whereas the vectors S and T lie within the chrominance (UV) plane. The S (skin) component is a linear combination of U and V obtained as the ‘average’ chrominance estimated from an assorted set human faces to achieve a reasonable generalisation. The third component, T, is defined as orthogonal to the YS plane. The results show the benefits obtained in digital watermarking by the new representation against the conventional approach. In fact, the sensitivity of the YST representation outperforms the conventional one in terms of objective (mean square error, peak signal-to-noise ratio) and subjective (video-quality metrics) indicators.

Effects of compression parameters on the perceived quality of video stream over a lossy Internet protocol network

We analyze the connection between viewer-perceived quality and encoding schemes. The encoding schemes depend on transmission bit-rate, MPEG compression depth, frame size and frame rate in a constant bit-rate (CBR) video transmission of a MPEG-2 video sequence. The compressed video sequence is transmitted over a lossy communication network with quality of service (QoS) and a certain Internet (IP) loss model. On the end-user side, viewer-perceived quality depends on changes in the network conditions, the video compression, and the video content complexity. We demonstrate that, when jointly considering the impact of coding bit rate, packet loss, and video complexity, there is an optimal encoding scheme, which also depends on the video content. We use a set of subjective tests to demonstrate that this optimal encoding scheme maximizes the viewer-perceived quality.

Error resiliency measure for RVLC codes

Video signals transmitted over error-prone wireless channels are often corrupted by bit errors. Due to their superior data recovery performance, the reversible variable length coding (RVLC) has been used as an error resiliency scheme in the MPEG-4 and H.263 video coding standards. In order to evaluate and compare the error resiliency performance of RVLC codes, we develop an error resiliency measure in this letter. Using this measure, different RVLC schemes are compared for MPEG-4 video sequences. The effects of propagating and nonpropagating errors are discussed as well.

Adaptive motion vector re-sampling for fast fade and dissolve transitions on MPEG video

Fade and dissolve transitions are two of the most frequently used special effects in video non-linear editing (NLE). In this paper, we propose an adaptive motion vector re-sampling (AMVR) algorithm to achieve fast fade and dissolve transitions on MPEG video sequences. Experimental results show that our algorithm greatly reduces the computational complexity while keeping the quality of the reconstructed edited video in comparison with conventional motion vector re-sampling (MVR) algorithms.

Combining Stream Table Experiments, High-tech Particle Analysis, and the Web to Help Geomorphology Students Evaluate Landform Evolution

Three sequential geomorphology labs introduce students to concepts of landform evolution, hypothesis testing, and grain-size analysis. Students combine qualitative observations with quantitative measurements from cutting-edge analytic equipment to critically evaluate their understanding of delta formation.In the first lab, students predict graphically how a stream-table delta will develop through time, and hypothesize how and why sediment grain sizes change across and within the delta. Digital Web cameras provide remote viewing and a time-lapse MPEG video sequence of delta formation.In the second lab, students compare the final landform with their original predictions of landform development. They sample delta topset, foreset, and bottomset beds for analysis on a laser particle-size analyzer to test their original hypotheses about grain-size distributions in the delta. Students operate the analyzer and produce grain-size distribution graphs of each sample. The graphs are posted to the course Web page, allowing students to compare visually the measured results to their Lab-1 predictions and to re-assess the processes of delta formation.The third lab is a field trip to local stranded late-Pleistocene deltas. By comparing the sediments of natural deltas to the stream-table version, students report improved understanding of the similarities, as well as the differences, in formation of each. Student assessment of the labs indicates they feel improved understanding of and interest in landform development compared to more traditional lecture and field trip-based instruction on the topic.

A Knapsack Model for Bandwidth Management of Prerecorded Multiple MPEG Video Sources

In this article we provide a framework for controlling the bit rate of multiple prerecorded MPEG video sequences by choosing the quantization factors assigned to individual sources in a way that the total mean square error at the output of the encoder is minimized. We propose and test a knapsack model for the selection of the quantization factors. Our computations based on a set of relatively diverse video sequences reveal that the proposed model achieves a high utilization of the available bandwidth and acceptable distortion levels without any data loss.

Video shot motion characterization based on hierarchical overlapped growing neural gas networks

Automatic video shot motion characterization is an important step in video indexing and retrieval after temporal video segmentation. This paper describes a hierarchical overlapped architecture (HOGNG) based upon the growing neural gas (GNG) network [7] to perform this task. The proposed architecture combines the unsupervised and supervised learning schemes in GNG. As higher-level GNGs overlap, the final classification is obtained by fusing the individual classifications generated by the top-level overlapping GNGs. In addition, we employ prefiltering and postfiltering for improving the classification accuracy. Experimental results are presented to show the good classification accuracy of the proposed algorithm on real MPEG video sequences.

AR-based quadratic modeling for GOP MPEG-encoded video traffic in ATM networks

Statistical analysis and performance modeling of compressed video traffic streams are efficient tools to estimate network resources and to predict network behavior under various conditions. Among current video traffic models, Autoregressive (AR) processes have been extensively used as good representation of variable bit rate video services, due basically to their simplicity and ease of computation. Recently, an elegant approach to the modeling of teleconferencing video has been proposed by Zhang in IEEE Trans. Circuits Syst. Video Technol. 9 (1999) p. 1130. This approach decomposes the traffic data into a linear combination of a number of chi-square sequences, each of which is obtained by passing a Gaussian AR process through a simple non-linearity. In this article, we first show that the model presented by Zhang is a special case of the general form of models represented by quadratic filters that are widely used in modern digital signal processing. Second, we extend Zhang's approach to model MPEG video traffic; an important full motion video source that exhibits dynamic and complex pattern. Specifically, we propose modeling MPEG video at GOP layer in ATM packet switching networks. This layer has an important feature in that it reflects the behavior of video scene activities. Finally, by using a wide variety of real MPEG video sequences, we experimentally demonstrate that the proposed GOP-based model approximates the real video traffic extremely well in terms of first and second order statistics as well as queuing performance.

Large-scale experimental study of Internet performance using video traffic

In this paper, we analyze the results of a seven-month real-time streaming experiment, which was conducted between a number of unicast dialup clients, connecting to the Internet through access points in more than 600 major U.S. cities, and a backbone video server. During the experiment, the clients streamed low-bitrate MPEG-4 video sequences from the server over paths with more than 5,000 distinct Internet routers. We describe the methodology of the experiment, the architecture of our NACK-based streaming application, study end-to-end dynamics of 16 thousand ten-minute sessions (85 million packets), and analyze the behavior of the following network parameters: packet loss, round-trip delay, oneway delay jitter, packet reordering, and path asymmetry. We also study the impact of these parameters on the quality of real-time streaming.

A scalable off-line MPEG-2 video encoding scheme using a multiprocessor system

Video compression plays a central role in a vast number of multimedia applications but its computational requirements overwhelm the capabilities of any present single processor system. In this paper, we explore the use of parallel machines like the Intel Paragon to compress MPEG-2 video sequences. The motivation is to build a production-based compression facility by exploiting the potential power of the available machine. Given a video sequence or a set of sequences, the aim of the parallel encoder is to achieve the maximum possible encoding rate. A collective scheduling scheme for the processors, I/O nodes, and disks is proposed that provides fast I/O, minimizes the idle times of processors, and enables the system to work in a highly balanced fashion. An efficient data layout scheme for storing video frames is also proposed in order for the I/O to sustain the desired data transfer rates. Using a small percentage of processors as the I/O nodes results in an efficient utilization of the system resources. As shown by experimental and analytical results, the encoding scheme is scalable and higher performance can be achieved with larger machines. The performance of the proposed scheme can be many times the real-time encoding rates with Standard Interface Format (SIF) and CCIR-601 video sequences. The experimental results indicate about two-fold gain in performance compared to the previous studies. Such a system is useful for the conversion of analog videos to compressed digital form in large studios, digital libraries, and other multimedia database environments. The proposed scheme partitions the system into groups of compute nodes, and I/O nodes, and can be easily extended to other MIMD machines or a set of networked workstations.

A markov—based algorithm for the generation of MPEG sequences matching intra— and inter—GoP correlation

AbstractThe development of sophisticated multimedia applications requires accurate performance evaluation tools to efficiently design and manage future high bandwidth networks. These tools have to be accurate, in order to closely match the statistical characteristics of network traffic, easy to implement, and efficient. VBR compressed video traffic is expected to represent most of the multimedia traffic loading networks in the immediate future, and the MPEG coding scheme will be the most widely used standard for many types of applications. Although many works in literature present models of video traffic, little effort has been devoted up to now to capturing one of the most important characteristics of MPEG video traffic: intra—GoP correlation. In this paper, after demonstrating that this correlation strongly affects the performance of a network loaded by MPEG video traffic, an accurate, fast and easy generation algorithm is proposed. The algorithm allows a sequence to be generated, imposing the Short Range Dependence (SRD), the Long Range Dependence (LRD) behavior and the probability density function of any given MPEG video sequence.

Modeling MPEG Coded Video Traffic by Markov-Modulated Self-Similar Processes

Markov modulated self-similar processes are proposed to model MPEG video sequences that can capture the LRD (Long Range Dependency) characteristics of video ACF (Auto-Correlation Function). The basic idea is to decompose an MPEG compressed video sequence into three parts according to different motion/content complexity such that each part can individually be described by a self-similar process. Beta distribution is used to characterize the marginal cumulative distribution (CDF) of the self-similar processes. To model the whole data set, Markov chain is used to govern the transitions among these three self-similar processes. In addition to the analytical derivation, initial simulations have demonstrated that our new model can capture the LRD of ACF and the marginal CDF very well. Network cell loss rate using our proposed synthesized traffic is found to be comparable with that using empirical data as the source traffic.

Nested auto-regressive processes for MPEG-encoded video traffic modeling

This paper presents a new traffic model for MPEG-encoded video sequences. The hybrid gamma/Pareto distribution is used for all three types of frames in MPEG-encoded video sequences, and the present model takes scene changes into account. The autocorrelation structure is modeled using two second-order auto-regressive (AR) processes nested with each other. One AR process is used to generate the mean frame size of the scenes to model the long-range dependence, and another AR process is used to generate the fluctuations within the scenes to model the short range dependence. The parameters of the AR processes are estimated from measurements of empirical video sequences. Simulation results show that the present model captures the autocorrelation structure in the empirical traces at both small and large lags. The MPEG traffic model presented in this paper is used to predict the queueing performance of single and multiplexed MPEG video sequences at an asynchronous transfer mode multiplexer. Comparison study shows that the present model provides accurate prediction for quality of service measures, such as cell-loss ratio under different traffic loads and various buffer sizes.

Adaptation of MPEG Video in ATM Networks Using Forward Loss/Error Recovery (FLER) Scheme

This paper describes the adaptation of MPEG video in ATM networks using a forward loss/error recovery (FLER) scheme to address the cell loss problem due to network congestion. An ATM adaptation layer (AAL) is proposed to facilitate the implementation of the FLER scheme using a two-dimensional error correction technique. Error control for a singlesegmentation and reassembly protocol data unit (SAR-PDU) is performed along the x -axis, while error control across a block of consecutive SAR-PDUs is performed along the y -axis. A new method using a real MPEG video sequence as the input source is proposed to evaluate the performance with the FLER scheme under various network conditions. On the other hand, subjective video quality evaluations have also been conducted. The results show that the FLER scheme is effective in solving the cell loss problem and thus enhances the QoS for MPEG video transmission in ATM networks.

Loss-resilient ATM protocol architecture for MPEG-2 video communications

MPEG-2 video communications over ATM networks is one of the most active research areas in the field of computer communications. In the transmission process of a variable bit rate video signal over an ATM network, cells are inevitably exposed to delays, errors, and losses due to the statistical multiplexing used in these networks. These phenomena affect the quality of the video signal, and without adequate measures to control the propagation of the impairments, the quality of the service may fall below acceptable levels. In this paper, we study the impact of cell losses on the quality of an MPEG-2 video sequence encoded in a variable bit rate mode. We introduce a set of control mechanisms at different levels of the protocol architecture to be used in MPEG-2-based video communications systems using ATM networks as their underlying transmission mechanism. Our results (using different video sequences) show the effectiveness to improve the video quality by using a structured set of control mechanisms to overcome for the loss of cells carrying VBR MPEG-2 video streams. We argue that in order to be able to create video systems able to cope with cell losses encountered in computer communications systems, a structured set of error-resilient protocol mechanisms is needed.

A Stochastic Framework for Optimal Key Frame Extraction from MPEG Video Databases

A video content representation framework is proposed in this paper for extracting limited, but meaningful, information of video data, directly from the MPEG compressed domain. A hierarchical color and motion segmentation scheme is applied to each video shot, transforming the frame-based representation to a feature-based one. The scheme is based on a multiresolution implementation of the recursive shortest spanning tree (RSST) algorithm. Then, all segment features are gathered together using a fuzzy multidimensional histogram to reduce the possibility of classifying similar segments to different classes. Extraction of several key frames is performed for each shot in a content-based rate-sampling framework. Two approaches are examined for key frame extraction. The first is based on examination of the temporal variation of the feature vector trajectory; the second is based on minimization of a cross-correlation criterion of the video frames. For efficient implementation of the latter approach, a logarithmic search (along with a stochastic version) and a genetic algorithm are proposed. Experimental results are presented which illustrate the performance of the proposed techniques, using synthetic and real life MPEG video sequences.

An efficient protocol architecture for error-resilient MPEG-2 video communications over ATM networks

MPEG-2 video communications over ATM networks is one of the most active research areas in the field of computer communications. In the transmission process of a variable bit rate video signal over an ATM network, cells are inevitably exposed to delays, errors and losses due to the statistical multiplexing used in these networks. These phenomena affect the quality of the video signal and without adequate measures to control the propagation of the impairments the quality of the service may fall below acceptable levels. In this paper, we study the impact of cell losses on the quality of a MPEG-2 video sequence encoded in a variable bit rate mode. We introduce a set of control mechanisms at different levels of the protocol architecture to be used in MPEG-2-based video communications systems using ATM networks as their underlying transmission mechanism. Our results (using different video sequences) show the effectiveness to improve the video quality by using a structured set of control mechanisms to overcome for the loss of cells carrying VBR MPEG-2 video streams. We argue that in order to be able to create video systems able to cope with cell losses encountered in computer communications systems, a structured set of error-resilient protocol mechanisms is needed.

Video retrieval based on scene change detection in compressed streams

This paper presents a new key frame extraction algorithm as well as a novel video-indexing scheme for a fast content-based browsing and retrieval in a video database. We first extract key frames by matching the AHIM (accumulated histogram intersection measure) of the DC image sequence constructed from the MPEG video sequence. Then we use the region segmentation-based projective histogram and its moments as database indices for video retrieval.

Quadtree structured region-wise motion compensation for video compression

The conventional variable-size block motion compensation technique, even though superior to the fixed-size block motion-compensation technique, cannot fully utilize the motion information of a frame for its partitioning. This paper presents a quadtree structured region-wise motion-compensation technique that utilizes more effectively the motion content of a frame in terms of the shape, size, and location of the partitioned regions. The proposed technique is based on a new coding scheme of the quadtree structure, where a two-bit code is used. The partitioning of a given frame is carried out through the processes of merging and combining. The merging process partitions the frame into a number of regions by carrying out all possible 4-to-1, 3-to-1, and 2-to-1 merges along the quadtree hierarchy according to some specified criteria, while the combining process combines some of the partitioned regions that have the same motion vector into a single region. The motion vectors of the resulting partitioned regions are coded by a new coding scheme that uses the temporal correlation of the motion fields. Test results of applying the proposed method on a number of MPEG video sequences are included. These results indicate that the proposed method can provide a significantly improved rate-distortion performance.