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A method is introduced to enhance the High Efficiency Video Coding early skip decision process. The proposed method exploits visual acuity and high-velocity motion perception of the human visual system (HVS). The method determines coding units where the HVS is unlikely to notice the changes and hence can be skipped. In this paper, the focus is mobile devices, such as smart phones, where displays are less than 5 in diagonal length and bandwidth availability is low. The proposed method exploits the mismatch between the video resolution, display resolution, and visual acuity of users. This method has very low impact on subjective quality while reducing encoding time for low bitrate environments. The proposed method reduces both encoding time and bitrate; the results show an average of 21.7% decrease in encoding time, 13.4% decrease in average bitrate, and very low impact on subjective quality ratings. The proposed methods can be adapted to decrease encoding time and bitrate in devices with lower resolution displays.

Rate control in video compression adjusts the encoding parameters to reach a certain target bitrate for the encoded video. State-of-the-art rate controllers for hybrid video coding typically employ content-dependent video bitrate models and video quality metrics (VQMs). To capture the content characteristics, temporal and spatial video activity measures are determined from the raw video using computationally complex algorithms that require access to the uncompressed source video. In automotive deployments, however, full access to the uncompressed source video and the internal functions of video encoders is typically not possible. As a remedy, in this paper, we present a low-complexity approach to estimate the temporal activity (TA) and spatial activity (SA) measures for videos that are captured by a front-facing camera of a vehicle, based on the context information of the vehicle. To this end, we exploit information about the dynamics of the vehicle and other vehicles in the field-of-view of the front-facing camera. We apply the estimated TA and SA values to a video bitrate model and an objective VQM and use these models to solve the rate control problem to determine the optimal encoding settings for given bitrate constraints. The proposed low-complexity solution offers a similar accuracy in achieving rate constraints and similar perceptual quality characteristics as a solution that uses the computed TA and SA values, with the advantage that no access to the uncompressed source video stream or the internal functions of the video encoder is required.

Temporal scalability is supported in scalable video coding (SVC) by means of hierarchical prediction structures, where the higher layers can be ignored for frame rate reduction. Nevertheless, this kind of scalability is not totally exploited by the rate control (RC) algorithms since the hypothetical reference decoder (HRD) requirement is only satisfied for the highest frame rate sub-stream of every dependency (spatial or coarse grain scalability) layer. In this paper we propose a novel RC approach that aims to deliver several HRD-compliant temporal resolutions within a particular dependency layer. Instead of using the common SVC encoder configuration consisting of a dependency layer per each temporal resolution, a compact configuration that does not require additional dependency layers for providing different HRD-compliant temporal resolutions is proposed. Specifically, the proposed framework for rate-controlled SVC uses a set of virtual buffers within a dependency layer so that their levels can be simultaneously controlled for overflow and underflow prevention while minimizing the reconstructed video distortion of the corresponding sub-streams. This in-layer multi-buffer approach has been built on top of a baseline H.264/SVC RC algorithm for variable bit rate applications. The experimental results show that our proposal achieves a good performance in terms of mean quality, quality consistency, and buffer control using a reduced number of layers. This work has been partially supported by the National Grant TEC2011-26807 of the Spanish Ministry of Science and Innovation. Publicado

The benefits of utilizing the spatial-frequency sensitivity of the human visual system in video coding have been known for decades and are incorporated into video standards, such as MPEG2, MPEG4, and H.264/AVC, as well as into still image-coding standards, such as JPEG and JPEG-2000. However, all of these standards utilize frequency weighting that is adaptive only at the picture level. In contrast with such picture-level adaptive frequency-weighting algorithms, we describe a coding approach in which a macroblock-level adaptive frequency-weighting (MBAFW) algorithm is used. We show that for the bitrate, quality levels, and resolutions typically associated with high-definition video, MBAFW can lead to overall bitrate reductions typically in the 5%-9% range over the methods used in state-of-the-art video-coding standards.

Hierarchical structure is a useful tool for providing the necessary scalability in adapting to the variety of channel environments. For schemes involving hierarchical picture structures, bit allocation, and rate control algorithms are vital components for improving video codec performance. Since conventional bit allocation schemes do not efficiently consider the hierarchical structure characteristics, it is difficult to optimize the video quality at an arbitrary bitrate. Similarly, conventional quantization parameter decision methods are not appropriate for controlling the bitrate generated by a codec using a hierarchical encoding structure. In this paper, we propose an effective bit allocation scheme that assigns the target number of bits to pictures or macroblocks (MBs) and improves the overall quality of images encoded by a hierarchical-based encoder. A rate control scheme is also proposed to ensure that the generated bitrate is equal to the assigned target bitrate. From the simulation results, the proposed schemes outperformed conventional methods from a rate-distortion perspective, by efficiently controlling the bitrate of the MB unit. The algorithms regulated the generated bits to achieve the target bits by using the proposed linear R-Q model.

A novel semi-fuzzy (SF) rate control algorithm (RCA) for variable bit rate (VBR) video applications is proposed. The proposed RCA is optimized to provide high quality compressed video bit streams in a wide operating range from constant quality to nearly constant bit rate. Thanks to a low degree of computational complexity, it is suitable for real-time applications of VBR video. The proposed RCA operates under given buffer size, delay and quality constraints. It provides a VBR video bit stream by controlling the quantization parameter (QP) on a picture basis. The QP is mainly controlled by a fuzzy rate controller and a deterministic quality controller, which are optimized such that they minimize the variation of quality to provide encoded video with high and stable visual quality. The proposed RCA has been implemented in an H.264/AVC video codec and the experimental results show that it provides a high-level average quality for encoded video while strictly obeying the buffering delay and quality constraints.

Congestion control of a variable bit-rate video stream crossing the Internet is crucial to ensuring the quality of the received video. When a fuzzy-logic congestion controller (FLC) changes the sending rate of a video transcoder, it does so without feedback of packet loss, using packet dispersion instead. Compared with the well-known TFRC and RAP controllers, the FLC's sending rate is significantly smoother, allowing it to more closely take up available bandwidth at a bottleneck link. There is an accompanying order of magnitude reduction in packet losses. Due to better utilization of the available bandwidth, video quality is improved over time by several decibels in low-packet-loss conditions. The strength of the FLC solution is demonstrated by the resulting video quality when typical Web traffic forms the background traffic. The FLC avoids any risk of congestion collapse through fairness to coexisting TCP flows and is robust to changes in path delay and router buffer configuration.

Providing quality of service (QoS) for Internet-based video streaming applications requires the server and/or client to be network-aware and adaptive. We present a dynamic rate and quality adaptation algorithm where the server varies its sending rate (without varying the quality level) to adapt to the network and client conditions and only as a last resort, does quality adaptation. We place the adaptation logic at the client since it has better knowledge about both the demand (buffer conditions, variable bit-rate requirements) and supply (network conditions). Our approach is unique because the server's sending rate is calculated based on the client's varying demand (consumption rate) and the network status. Also, we do not model the network as a black-box but instead augment endpoint observations with a feedback from the network to represent its status more precisely. To make an informed adaptation decision, the client requires sizes of all frames in the variable bit rate video. But the overhead involved in sending this metadata is significant. So we propose a lossy compression technique to reduce the amount of control information and consequently the overhead. We also present a scheduling algorithm, dynamic scheduling algorithm for reduced trace delivery (DART), to deliver the compressed control information to the client. This algorithm can be used to deliver any form of metadata (like subtitles, alerts, etc.), especially in applications like IP-TV. Simulations show that the proposed techniques can significantly improve user perceived QoS when compared to other popular adaptation methods.

In this paper, we investigate optimal frame-selection algorithms based on dynamic programming for delivering stored variable bit rate (VBR) video under both bandwidth and buffer size constraints. Our objective is to find a feasible set of frames that can maximize the video's accumulated motion values without violating any constraint. It is well known that dynamic programming has high complexity. In this research, we propose to eliminate nonoptimal intermediate frame states, which can effectively reduce the complexity of dynamic programming. Moreover, we propose a reverse frame selection (RFS) algorithm, where the selection starts from the last frame and ends at the first frame. Compared with the conventional dynamic programming-based forward frame selection, the RFS is able to find all of the optimal results for different preloads in one round. We further extend the RFS scheme to solve the problem of frame selection for VBR channels. In particular, we first perform the RFS algorithm offline, and the complexity is modest and scalable with the aids of frame stuffing and nonoptimal state elimination. During online streaming, we only need to retrieve the optimal frame-selection path from the pregenerated offline results, and it can be applied to any VBR channels as long as the VBR channels can be modeled as piecewise CBR channels. Experimental results show good performance of our proposed algorithms

Two schemes are proposed to efficiently compress video contents into bitstreams that support drift-free switching at predictive frames. They are inspired by the original SP coding scheme presented in the early H.26L. First, we propose a Flex SP coding scheme in which the prediction signal of the SP frame is directly subtracted from the input without quantization and de-quantization. The decoded video quality of the Flex SP scheme is significantly improved when additional inverse discrete cosine transform (DCT) and post-filter are provided. Then, the Hybrid SP scheme is presented to further improve the quality of the display image, as well as the reconstructed reference, by defining two coding modes for each DCT coefficient. Moreover, a rate-distortion algorithm is proposed to determine the coding mode for each coefficient. The bitstreams generated by the two proposed schemes can be decoded successfully by a decoder that complies with MPEG-4 AVC/H.264. In addition, we also investigate how to choose the quantization parameters for switching. An empirical method is proposed to achieve a good tradeoff between high coding efficiency of SP frames and small size of switching bits.

In recent years, a number of sophisticated architectures have been proposed to provide video-on-demand (VoD) service using multicast transmissions. Compared to their unicast counterparts, these multicast VoD systems are highly scalable and can potentially serve millions of concurrent users. Nevertheless, these systems are designed for streaming constant-bit rate (CBR) encoded videos and thus cannot benefit from the improved visual quality obtainable from variable-bit rate (VBR) encoding techniques. To tackle this challenge, this paper presents a turbo-slice-and-patch (TSP) algorithm to support VBR video streaming in a multicast VoD system. Results obtained from trace-driven simulation of 300 VBR videos show that serving VBR videos with the TSP algorithm increases the average latency by only 9% compared to the CBR case with the same average video bit rate. Moreover, in 165 out of the 300 video titles, the TSP algorithm actually outperforms the CBR equivalent by shortening the latency by 0.04%-99%. Given that we can achieve similar visual quality by encoding VBR video at half the average rate of CBR video, this TSP algorithm can potentially serve VBR videos with more consistent visual quality and with less resource compare to CBR-based video streaming systems.

In variable-bit-rate video coding, the video is preprocessed to collect sequence-level statistics, which are used for global bit allocation in the actual encoding stage to obtain a smoothed video presentation quality. However, in real-time video recording and network streaming, this type of two-pass encoding scheme is not allowed because the access to future frames and global statistics is not available. To address this issue, we introduce the concept of low-pass filtering of rate-distortion functions and develop a smoothed rate control (SRC) framework for real-time video recording and streaming. Theoretically, we prove that, using a geometric averaging filter, the SRC algorithm is able to maintain a smoothed video presentation quality while achieving the target bit rate automatically. We also analyze the buffer requirement of the SRC algorithm in real-time video streaming, and propose a scheme to seamlessly integrate robust buffer control into the SRC framework. The proposed SRC algorithm has very low computational complexity and implementation cost. Our extensive experimental results demonstrate that the SRC algorithm significantly reduces the picture quality variation in the encoded video clips.

Variable-bit-rate (VBR) encoded videos can provide a more consistent visual quality than constant-bit-rate (CBR) encoded videos. However, the long-range bit-rate variations in VBR videos make it difficult to efficiently provide quality-of-service control in a video-on-demand system. Existing scheduling algorithms such as Optimal Smoothing, which requires both downward and upward bandwidth reallocations to adapt to the video bit-rate variations, simply cannot guarantee video delivery in networks with mixed video and data traffic. This study tackles this limitation by investigating a new scheduling algorithm with monotonic-decreasing rate allocations for scheduling video data transmissions. By eliminating upward bandwidth reallocations, the proposed scheduler can guarantee video delivery even in the presence of other data traffic in the same network. Moreover, results show that the proposed scheduler can achieve such performance guarantee without tradeoff in performance or resource requirements. This work presents this new monotonic-decreasing rate scheduler, analyzes its fundamental properties, and evaluates its performance using a large number of real-world VBR video traces (274 DVD movies) in extensive trace-driven simulations.

The MPEG-4 standard enables the representation of video as a collection of objects. This paper describes an automatic system that exploits such a representation. Our system consists of two parts: real-time content extraction algorithms and a real-time multi-object rate control method. We present two approaches to content extraction: foreground segmentation based on two cameras and face segmentation based on a single camera. The main contributions of this paper are: 1) under a stereo camera setup, we improve a disparity estimation algorithm to obtain crisp and smooth boundaries of foreground objects; 2) for a single camera scenario, we propose a novel algorithm for face detection and tracking, combining facial color and structure information; and 3) we develop a constant-quality variable bitrate (CQ-VBR) control algorithm that guarantees the quality specification for each object obtained from the two content extraction methods. Both segmentation algorithms run in real-time on a low-cost media processor, and have been tested extensively in various indoor environments. The CQ-VBR control algorithm is a useful tool for the evaluation of object-based coding. For low-bit-rate applications, we can achieve significant reduction in the overall bitrate, while maintaining the same visual quality of the foreground/face object as compared to conventional frame-based coding. Based on tests conducted on several sequences of different complexity levels, the bit-rate savings can be up to 48%. The satisfactory foreground segmentation (results presented) permits porting a live foreground object into arbitrary scenes to create composite video.

Interactive video services such as video conferencing, distance learning, and online video games over the Internet and wireless networks are becoming increasingly prevalent. Because of limited bandwidth on networks and the bandwidth-hungry nature of video, interactive video requires extremely efficient resource management to gain real-time performance. Unlike pregenerated video whose traffic profiles can be computed in advance, efficiency and accuracy of dynamic resource allocation methods for interactive video depend critically on the performance of traffic prediction. Using either traffic data or image features, existing traffic prediction schemes can only provide a short-term traffic prediction. Based on a three-dimensional object's motion, this paper presents a new bandwidth prediction approach for video conferencing. We show that there is a strong correlation between video conferencing traffic and real motion of objects. The real motion can be predicted by the powerful technique Kalman filtering, and the estimated motion is used to make a long-term bandwidth prediction. The new traffic prediction model is tested and compared with the frame-based adaptive normalized least mean square error linear predictor and optical flow-based method with Kalman filtering. Experimental results show that our proposed traffic prediction model achieves much higher accuracy in long-term traffic prediction, which provides the possibility for networks to allocate resources efficiently for video conferencing services.

A novel MPEG-4 compressed domain video watermarking method is proposed and its performance is studied at video bit rates ranging from 128 to 768 kb/s. The spatial spread-spectrum watermark is embedded directly into compressed MPEG-4 bitstreams by modifying DCT coefficients. A synchronization template combats geometric attacks, such as cropping, scaling, and rotation. The method also features a gain control algorithm that adjusts the embedding strength of the watermark depending on local image characteristics, increasing watermark robustness or, equivalently, reducing the watermark's impact on visual quality. A drift compensator prevents the accumulation of watermark distortion and reduces watermark self-interference due to temporal prediction in inter-coded frames and AC/DC prediction in intra-coded frames. A bit-rate controller maintains the bit rate of the watermarked video within an acceptable limit. The watermark was evaluated and found to be robust against a variety of attacks, including transcoding, scaling, rotation, and noise reduction.

We formulate a congestion control problem for multipoint videoconferencing by introducing the concept of generalized fairness. A numerical method is provided to solve such a congestion control problem. The proposed method is much simpler than an earlier proposed method. This is desirable because congestion control is executed in real time.

We propose a novel variable bit rate (VBR) algorithm that adopts two-pass encoding to implement high-performance coding for fixed-size storage applications. In the first-pass encoding, we use the original frame as the reference for motion estimation. This way, we are able to obtain the exact relationship between the amount of bits generated for each frame (rate) and each possible quantization factor (Q) so that an R-Q function can be built. The corresponding computational expense is virtually the same as a typical VBR encoder. With this R-Q function, we can optimize the quantization factor for each frame throughout the entire sequence based on the constraints in total storage size and decoder buffer size before the second-pass encoding is executed. This procedure not only guarantees full use of the fixed storage size for the compressed bitstream, but also prevents the decoder buffer from underflowing. Unlike a typical constant bit rate (CBR) decoder, this VBR decoder is capable of preventing the buffer from overflowing by introducing the pausing operation at some designated time. Because the quantization factor optimization is a simple table lookup, the computational requirement is minimized. In the second-pass encoding, the estimated quantization factors for all the frames through the above procedures is used to encode the entire video sequence as a free VBR encoder. Experimental results on real video sequences show that the proposed VBR encoding can provide more consistent visual quality and an improved coding efficiency. The application of the proposed VBR coding scheme includes video streaming over the Internet, digital versatile disk, digital library, and video on demand.

State-of-the-art digital video compression produces bursty, variable bit rate video. The bursty nature of compressed video raises challenges in the design of video servers. In this paper, we first present a method for the efficient retrieval of bursty video data from the disk system to the memory of a digital video server. For a single video stream, the proposed retrieval schedule minimizes the buffer requirement for continuous retrieval, given that a fixed disk bandwidth is reserved for the entire duration of retrieval. Secondly, we present an optimal resource-reservation algorithm for multiple video streams based on the proposed retrieval schedule. The resource-reservation algorithm maximizes the number of bursty video streams that ran be supported by a video server given any disk bandwidth and memory resource. Thirdly, we present a progressive display scheme for scalable video that is based on the retrieval schedule and resource-reservation algorithm. Performance evaluations based on simulations using MPEG-2 trace data are presented. For a personal computer with four disks and a memory resource of 120 MB, our approach can support 50%-275% more video streams than previously proposed approaches, depending on the pre-fetch delay that users are willing to tolerate in interactive viewing of videos.

It has been previously reported that variable bit rate video traffic displays signs of long-range dependence (Beran et al. 1995, and Garrett 1993), which is defined within the framework of weak stationarity. The concept of weak stationarity is of fundamental practical interest, because it implies the existence and independence with time of mean and autocovariance. Since mean and variance might be used as parameters for policing the traffic stream on a broadband communication network, it is important to verify the underlying assumption of weak stationarity. The results presented in this paper strongly call into question this assumption. As a possible explanation, we offer shifting level processes which are asymptotically weakly stationary for infinite sample sizes.

Variable bit-rate (VBR) MPEG video traffic is highly bursty due to group of pictures structure, and shows time-variant statistical characteristics due to scene changes. These characteristics make it more difficult to manage network resources, and leads to the significant reduction in network utilization. We deal with the issues related to efficiently transmitting VBR MPEG video traffic over asynchronous transfer mode networks, while maintaining consistent visual quality and improving network utilization on the basis of real-time applications. First, we propose a joint encoder and channel-rate control scheme that comply with not only negotiated traffic parameters, but also constraints imposed by encoder and decoder buffers. Second, we propose a dynamic bandwidth renegotiation method by combining the above scheme with a traffic smoothing method that can make the peak rate close to the sustainable rate. The efficiencies of the proposed methods are compared with a few other competitive schemes such as transmission methods for unconstrained VBR and the constant bit-rate scheme with average bandwidth equal to that of the proposed methods.

The performance evaluation of broadband networks requires statistical analysis and modeling of the actual network traffic. Since multimedia services, and especially variable bit rate (VBR) MPEG-coded video streams are expected to be a major traffic component carried by these networks, modeling of such services and accurate estimation of network resources are crucial for proper network design and congestion-control mechanisms that can guarantee the negotiated quality of service at a minimum cost. The layer modeling of MPEG-1 coded video streams and statistical analysis of their traffic characteristics at each layer is proposed, along with traffic models capable of estimating the network resources over asynchronous transfer mode (ATM) links. First, based on the properties of the entire MPEG-1 sequence (frame layer signal), a model (Model A) is presented by correlating three stochastic processes in discrete time (autoregressive models), each of which corresponds to the three types of frames of the MPEG encoder (I, P, and B frames). To simplify the traffic Model A and to reduce the required number of parameters, we study the MPEG stream at a higher layer by considering a signal, which expresses the average properties of I, P, and B frames over a group of picture (GOP) period. However, models on this layer cannot accurately estimate the network resources, especially in multiplexing schemes. For this reason, an intermediate layer is introduced, which exploits and efficiently combines information of both the aforementioned layers, producing a model (Model B), which requires much smaller number of parameters than Model A and simultaneously provides satisfactory results as far as the network resources are concerned. Evaluation of the validity of the proposed models is performed through experimental studies and computer simulations, using several long duration VBR MPEG-1 coded sequences, different from that used in modeling. The results indicate that both Models A and B are good estimators of video traffic behavior over ATM links at a wide range of utilization.

Modeling variable-bit-rate (VBR) video source traffic is a crucial issue to evaluate the end-to-end performance of transmitting video signals over asynchronous transfer mode (ATM) networks. Difficulties in source modeling arise from the fact that VBR video source traffic usually follows a gamma distribution with high correlation among adjacent data. Many researchers adopt autoregressive (AR) models driven by a Gaussian error process to account for such correlation. The problem is: due to the closure property of the Gaussian distribution, the traffic so generated is Gaussian rather than gamma. As a remedy, some researchers directly consider gamma AR models instead. Unfortunately, the trouble arises from the fact that the closure property does not apply to gamma distributions, and thus, the linear operation performed by an AR model fails to produce gamma traffic. In this paper, we present a new technique that is capable of generating gamma-distributed traffic with arbitrary correlation while retaining the computational efficiency of Gaussian AR models. The central idea is to decompose given gamma traffic into a linear combination of a number of /spl lambda//sup 2/(1) sequences, and each of these latter processes can be easily obtained from a Gaussian AR process through a simple nonlinear operation. Results based on actual video teleconference data are presented to verify the validity of the new algorithm.

Several works have concluded that the number of cells per frame of variable bit-rate (VBR) video teleconference follows a gamma distribution. But few video models meet this characteristics. We propose a novel video model, called first-order autoregressive (AR) gamma sequence, in which random variables are marginally distributed as gamma variables. We give the definition of a GAR model and a simple realization method of GAR(1). Parameter estimation methods are studied, too. Simulation results show that our model can meet the characteristics of VBR video better than existing models.

Examines the transmission of variable bit-rate (VBR) H.261 video over a mixed traffic (video/inter-LAN) integrated services frame relay (FR) network. We introduce a modified H.261 codec that produces VBR output and show that parsing of the video bit stream at group of blocks (GOB) boundaries produces variable length FR packets well suited to the network. We demonstrate that GOB-level video traffic requires a more sophisticated statistical model of the resulting data stream than the frame-level models. The transform expand sample (TES) method is used to obtain an accurate model of the autocorrelation and the marginal probability distribution of the bit-rate variations at the GOB level. A simple and effective methodology is introduced for capturing the periodic components that are present in the GOB-level autocorrelation. The methodology is extended to permit simulations of VBR codecs in which the codec quantization step size is adjusted in response to prevailing network conditions. We show that the quality of service requirements of VBR video can be met by using the FR backward explicit congestion notification (BECN) facility in conjunction with a modified H.261 codec whose rate is controlled by the congestion notification. We also show that the performance of the control mechanism is significantly influenced by a subset of network threshold and codec control parameters which are identified using 2/sup k/ factorial analysis techniques. We obtain optimal ranges of values for these parameters using mean field annealing. Variable quantization rate control may be more effective for this purpose than variable frame rate control.

Rate control is considered an important issue in video coding, since it significantly affects video quality. We discuss joint encoder and channel rate control for variable bit-rate (VBR) video over packet-switched ATM networks. Since variable bit-rate traffic is allowed in such networks, an open-loop encoder without rate control can generate consistent quality video. However, in order to improve the statistical multiplexing gain (SMG), an encoder buffer is essential to meet traffic constraints imposed by networks and to smooth the highly variable video bitstream. Due to the finite buffer size, some forms of encoder rate control have to be enforced, and consequently, video quality varies. We argue that a rate control scheme has to balance both issues of consistent video quality on the encoder side and bitstream smoothness for the SMG on the network side. We present a joint encoder and channel rate control algorithm for ATM networks with leaky buckets as open-loop source flow control models. The algorithm considers constraints imposed by the encoder and decoder buffers, the leaky bucket control, traffic smoothing, and rate control. The encoder rate control is separated into a sustainable-rate control and a unidirectional instantaneous-rate control. It can improve the problem of leaky bucket saturation exhibited in previous works. Experimental results with MPEG video are presented. The results verify our analysis and show the effectiveness of the proposed algorithm.

We consider the placement of scalable video data on single and multiple disks for storage and real-time retrieval. For the single-disk case, we extend the principle of constant frame grouping from constant bit rate (CBR) to variable bit rate (VBR) scalable video data. When the number of admitted users exceeds the server capacity, the rate of data sent to each user is reduced to relieve the disk system overload, offering a graceful degradation in comparison with nonscalable data. We examine the qualities of video reconstructions obtained from a real disk video server and find the scalable video more visually appealing. In the VBR case, scalability is also used to improve interactivity by reducing the delay associated with using interactive functions in a predictive admission control environment. Finally, we consider the multiple disk scenario and prove that periodic interleaving results in lower system delay than striping in a video server using round-robin scheduling. We verify the results through detailed simulation of a four-disk array.

Many studies have been conducted involving the transport of constant and variable bit rate MPEG-2 video in asynchronous transfer mode (ATM) networks; however, many of these studies have considered fairly homogeneous scenarios in which the only other traffic present in the ATM network, if any, are other MPEG-2 video sources. In this study the requirements of supporting MPEG-2 video communications in an ATM network under unloaded and heavily loaded network conditions, in which the generated traffic sources are bursty in nature, are considered. To complete the study an experimental video on demand (VoD) testbed, developed as part of a collaborative research effort between the Communications Research Center of Canada (CRC), Nortel and the University of Ottawa, was employed. To determine the characteristics of the MPEG-2 video traffic generated by the VoD application in the ATM network in the presence of other traffic, cell interarrival time measurements and cell rate snapshots at the ATM cell level were considered. Results obtained show that the end-to-end flow control implemented in the application layer in the video-on-demand (VoD) system and the traffic controls implemented intermediate network elements (e.g., routers, switches) have significant impacts on the characteristics of the MPEG-2 traffic carried in the ATM network. Moreover, the impact of the intermediate network elements on the characteristics of the MPEG-2 traffic increases with the amount of non-MPEG-2 video.

When a Banyan switch is used to switch variable bit rate (VBR) video, some video packets may not be switched before their deadlines because the VBR video sources may temporarily generate heavy traffic or they only generate moderate traffic but some video packets encounter internal blocking in the switch. Therefore, some video packets may be discarded. We determine the condition of packet loss and then derive the packet loss probability. Based on this result, we perform admission control to determine whether a given video session can be admitted while the resulting packet loss probability is still small enough to guarantee a good image quality.

Scalability refers to the ability to modify the resolution and/or bit rate associated with an already compressed data source in order to satisfy requirements which could not be foreseen at the time of compression. A number of researchers have already demonstrated the feasibility of efficient scalable image and video compression. The principle focus of this paper is to describe data structures for highly scalable compressed video, which are able to support simple, generic scaling approaches for both constant bit rate and constant distortion scaling criteria. Interactive video material presents particular challenges when the data stream is to be scaled to maintain an approximately constant level of distortion, rather than just a constant bit rate. Special attention is paid, therefore, to the development of generic, robust scaling algorithms for such applications. The data structures and scaling methodologies developed are particularly appealing for the distribution of highly scalable compressed video over heterogeneous media, because they simultaneously support both variable bit rate (VBR) and constant bit rate (CBR) services with a wide range of available service qualities, using only simple, generic mechanisms for scaling. The performance of the proposed scaling methodologies is experimentally investigated using a highly scalable video compression algorithm, which is able to achieve comparable compression performance to that of the inherently nonscalable MPEG-1 compression standard.

The algorithmic architecture and performance of a video coder are described that switches between the model-based and H.261 modes, depending on image content. The switching criterion incorporates measures of both picture quality and bit rate. The model-based mode uses generalized cylindrical models and a 3D matching technique to estimate motion. The coder was tested with four different image sequences in CBR and VBR operational modes: the performance was generally superior, and in some cases significantly superior, to that of a free-running H.261 coder operating on the same sequences. The switched architecture represents a possible route for the integration of model-based coding with H.261 to give improved performance at very low bit rates. >

Many techniques have been proposed for modeling source rates generated by variable bit rate video coders. However, little work has been done to verify these models, especially in the area of measuring the quality of their predictions for network performance and the grade of service experienced by a customer. In this paper, we summarize the previous work in this area, highlight some of the difficulties in effectively verifying these models, and suggest methods by which source rate models for VBR video might be more effectively verified in the future. In addition to studying the problem of model verification, a new model is proposed. Using this model, a video sequence is characterized by four parameters. As in previous cases, the number of bits generated by the coder for a sequence of video frames is modelled. The new model differs from previous models in that this sequence is not Markovian. >

A variable-bit-rate coding algorithm based on motion-adaptive discrete cosine transform (DCT) is investigated for asynchronous transfer mode (ATM) environments in broadband integrated-services digital networks (B-ISDN). The algorithm effectively reduces the bit rate, in particular, for HDTV-picture sources with little motion. Adaptive two-layered coding, an ATM cell matrix for error correction, and a block interleave for error concealment are proposed to keep picture quality high by compensating for ATM cell loss. A feedforward control scheme for variable-length coding (VLC), a multimode quantization that restricts peak bit rate and average bit rate, is also proposed for traffic control. Experimental hardware is shown to reduce the coding bit rate for pictures of HDTV conference applications to peak bit rate of 65-Mb/s and an average bit rate of 10-20-Mb/s in ATM environments. >

A motion-adaptive variable-bit-rate (VBR) video codec is considered, and a motion-classified model is developed to represent the characteristics of various classes of motion activities, including scene changes. The codec switches between interframe, motion-compensated, and intraframe coding corresponding to low, medium, and high amounts of motion and scene changes, respectively. The model captures the motion of various video scenes by providing the statistics of VBR-coded video traffic through a first-order autoregressive process with time-varying parameters. The parameters of this model are obtained from a VBR-coded sample video sequence with the objective of matching the bit-rate distribution and the autocorrelation among the bit rates. The validity and accuracy of the model are evaluated, and the characteristics of aggregated traffic sources obtained with the model are discussed. >

Results are presented of a simulation study of the potential multiplexing gains from using variable-bit-rate (VBR) encoding to multiplex video teleconferencing traffic over an asynchronous transfer mode (ATM) network. Simulated traffic from several video teleconferences is fed into a buffer and multiplexed onto a higher-speed output line. The cell loss resulting from buffer overflow is observed. The major results are as follows: (1) the spacing between cells has a large role in determining the aggregate cell loss rate seen by a collection of calls. The cell loss rate is reduced when either the frame start times are evenly spaced or cells are evenly distributed in the video frame. (2) After the cell loss rate becomes nonnegligible, it grows rapidly as a function of the number of access lines. (3) The cell losses are not distributed uniformly over time but are clustered. A consequence is that the average time between clusters of cell loss and the time to first loss is greater than if the losses were spaced uniformly. (4) A simple model is found to describe when a cluster of cell losses occurs, the duration of the cluster, and how many cells are lost in the cluster. >

Constraints on the encoded bit rate of a video signal that are imposed by a channel and encoder and decoder buffers are considered. Conditions that ensure that the video encoder and decoder buffers do not overflow or underflow when the channel can transmit a variable bit rate are presented. Using these conditions and a commonly proposed network-user contract, the effect of a (BISDN) network policing function on the allowable variability in the encoded video bit rate is examined. It is shown how these ideas might be implemented in a system that controls both the encoded and transmitted bit rates. The performance of video that has been encoded using the derived constraints for the leaky bucket channel is presented. >