Group Of Pictures Research Articles

Content-based group-of-picture size control in distributed video coding

Controlling the group of picture (GOP) size in distributed video coding (DVC) is a difficult but important task since it has a direct impact on the coding performance. This paper presents a framework to adaptively control the size of GOPs in a Wyner–Ziv encoder by means of encoder-side decisions based on support vector machines (SVM) that uses simple features extracted from the original video content. To train the SVM, firstly this work proposes how to compute the sequence of GOP sizes with the best rate-distortion performance given the set of GOP sizes that can be used during the encoding process. Then, an algorithm based on the previously trained SVMs is presented to control the actual GOP size each time a new decision can be taken at the encoder. Results show that the proposed algorithm can achieve a rate distortion performance close to the ideal one. Moreover, comparisons with a reference adaptive GOP size selection algorithm in the literature shows gains up to 2dB PSNR in the best conditions.

A novel macroblock level rate control method for stereo video coding.

To compress stereo video effectively, this paper proposes a novel macroblock (MB) level rate control method based on binocular perception. A binocular just-notification difference (BJND) model based on the parallax matching is first used to describe binocular perception. Then, the proposed rate control method is performed in stereo video coding with four levels, namely, view level, group-of-pictures (GOP) level, frame level, and MB level. In the view level, different proportions of bitrates are allocated for the left and right views of stereo video according to the prestatistical rate allocation proportion. In the GOP level, the total number of bitrates allocated to each GOP is computed and the initial quantization parameter of each GOP is set. In the frame level, the target bits allocated to each frame are computed. In the MB level, visual perception factor, which is measured by the BJND value of MB, is used to adjust the MB level bit allocation, so that the rate control results in line with the human visual characteristics. Experimental results show that the proposed method can control the bitrate more accurately and get better subjective quality of stereo video, compared with other methods.

Visual quality assessment after network transmission incorporating NS2 and Evalvid.

On the basis of Evalvid tool integrated in NS2 (Network Simulator version 2), the paper gets new set of tools, myEvalvid, to establish the simulation and evaluation platform for multimedia transmission. Then the paper investigates the effects of various influence factors when multimedia information is transmitted in the network and the relationships among these factors. Based on the analysis, the paper gets different evaluation models, respectively. In this paper, we study the impact on performance of several basic source and network parameters of video streams, namely, GOP (Group of Pictures) pattern, compression quantitative parameters, packet length, and packet error rate. Simulation results show that different parameters lead to different distortion levels which are calculated according to the reconstruction images at the receiver and the original images. The experimental results show that the video transmission and quality evaluation model we designed can evaluate multimedia transmission performance over complex environment very well.

Distributed video coding with block mode decision to reduce temporal flickering

The common distributed video coding (DVC) systems treat input video frames group by group. In each group of pictures (GOP), usually the first frame, called key frame, is intra-coded and the others are Wyner-Ziv (WZ)-coded. This GOP coding structure presents a fixed and inefficient coding mode switch (key or WZ) at group boundaries, thus preventing a DVC system from adapting the rate-distortion (R-D) performance to varying video content. In this work, a structure of temporal group of blocks (TGOB) with dynamic coding mode (key/WZ) decision is presented. This dynamic TGOB coding architecture determines each image block to be a key block or a WZ block based on spatiotemporal image analysis, resulting in a mode switch of fine granularity in both the spatial and temporal domains. As a consequence, not only the overall coding efficiency is improved, but also the temporal flickering artifacts for the reconstructed video are reduced substantially. Experimental results show that our proposed DVC scheme with block mode decision achieves up to 2.85 dB of quality gain and also up to 51% of temporal flickering reduction, compared to the well-known DISCOVER system.

Balanced Parallel Scheduling for Video Encoding with Adaptive GOP Structure

Due to the nature of a dynamic group of picture (GOP) structure, parallel scheduling for video encoding becomes challenging. To address this, the balanced frame-level parallel scheduling algorithms are developed. The proposed approaches first determine the frame priority and then the thread priority assignment for scheduling. The concept of the algorithms lies in the analysis of coding complexity, temporal influence, and the required temporal burden to finish coding. To complete the scheduling with the dynamic GOP structure, a block-based abrupt and gradual scene change detection algorithm is also proposed to determine the GOP structure adaptively. The experiments show that the scheduling performance is close to the optimal. In addition, the concept of batch processing is incorporated so that the required buffer can be reduced.

Raptor Codes Based Unequal Protection for Compressed Video According to Packet Priority

Raptor codes are state-of-the-art forward error correction (FEC) solutions for multimedia transmission, which have been applied to unequal error protection (UEP) of multi-layered media such as scalable video coding. In this paper, we address the problem of UEP for single-layered video over packet erasure channels. By exploiting the different priorities of video packets inside a group of pictures (GOP) and making full use of the good characteristics of standardized Raptor codes at large block length, we propose an optimized UEP framework for single-layered video and develop an efficient algorithm to solve it. Simulation results show that significant gains can be obtained by our method in case of packet losses.

Scene content driven FEC allocation for video streaming

Unequal error protection schemes applied on video data streams, considering varying importance of data packets over a group of pictures (GOP), are more efficient in terms of rate-distortion performance at different loss rates. Importance ordering policy adopted so far, mostly considered frame positions within a GOP. In the present work, we offer significant importance to the packets containing scene-transition frames, as these should be better error protected. We adopt a strategy of Forward Error Correcting (FEC) Code allocation, based on the minimization of end-to-end distortion up to the decoder, assuming that error concealment is adopted at the decoder. Two FEC allocation strategies are proposed within the Block of Packets (BOP) structure — one is an iterative modified hill climbing approach and the other is a reduced complexity heuristic approach. The Gilbert–Elliot model is used for the modeling of transmission channel. The proposed FEC allocation schemes outperform existing FEC allocation schemes in terms of PSNR for sequences with and without transitions, when transmitted over lossy channels.

WCCP: A congestion control protocol for wireless multimedia communication in sensor networks

The growing interest in applications of Wireless Multimedia Sensor Networks (WMSNs) imposes new challenges on congestion control protocols in such networks. In this paper, we propose a new content-aware cross layer WMSN Congestion Control Protocol (WCCP) by considering the characteristics of multimedia content. WCCP employs a Source Congestion Avoidance Protocol (SCAP) in the source nodes, and a Receiver Congestion Control Protocol (RCCP) in the intermediate nodes. SCAP uses Group of Picture (GOP) size prediction to detect congestion in the network, and avoids congestion by adjusting the sending rate of source nodes and distribution of the departing packets from the source nodes. In addition, RCCP monitors the queue length of the intermediate nodes to detect congestion in both monitoring and event-driven traffics. Moreover, to improve the received video quality in base stations, WCCP keeps the I-frames and ignores the other less important frame types of compressed video, in the congestion situations. The proposed WCCP protocol is evaluated through simulations based on various performance metrics such as packet loss rate, frame loss rate, Peak Signal-to-Noise Ratio (PSNR), end-to-end delay, throughput, and energy consumption. The results show that WCCP significantly improves the network performance and the quality of received video in the sink nodes, and outperforms the existing state-of-the-art congestion control protocols.

Performance Optimization of Video Coding Process on Multi-Core Platform Using Gop Level Parallelism

High definition video applications often require heavy computation, high bandwidth and high memory requirements which make their real-time implementation difficult. Multi-core architecture with parallelism provides new solutions to implementing complex multimedia applications in real-time. It is well-known that the speed of the H.264 encoder can be increased on a multi-core architecture using the parallelism concept. Most of the parallelization methods proposed earlier for these purposes suffer from the drawbacks of limited scalability and data dependency. In this paper, we present a result obtained using data-level parallelism at the Group-Of-Pictures (GOP) level for the video encoder. The proposed technique involves each GOP being encoded independently and implemented on JM 18.0 using advanced data structures and OpenMP programming techniques. The performance of the parallelized video encoder is evaluated for various resolutions based on the parameters such as encoding speed, bit rate, memory requirements and PSNR. The results show that with GOP level parallelism, very high speed up values can be achieved without much degradation in the video quality.

An Enhanced Rate Control Initialization Method for H.264 based on Image Quality Balance of GOP Using Support Vector Machines

In this paper, we propose an enhanced method of initializing the quantization parameter ( QP ) in H.264 rate control algorithm based on image quality balance of GOP (Group of Pictures) using support vector machines ( SVM s). Primarily, we analyze characteristics of some typical video sequences by motion vectors. And then we choose four video sequences with different characteristics and computer their spatial and temporal complexities and the optimal initial QP s which can guarantee to generate video sequences with consistent quality by minimizing the variation of QP s in a GOP , while ensuring the actual encoding bit rate closer to the target bit rate in various bit rates by proposed selection method of optimal initial QP . We utilize SVM s that can detect the optimal parameters by genetic algorithm to train the regression function of the extracted features that are the spatial and temporal complexities as well as given the target bit rates of sample video sequences and target that is optimal initial QP s. When any video sequence is given under any target bit rate, its spatial complexity is calculated and mapped to one of four samples through the proposed mapping method. Finally, its optimal initial QP is determined by regression function according to the mapped spatial complexity, corresponding temporal complexity of sample video sequence and given target bit rate

Efficiency of Dynamic GOP Length in Video Stream

Multiple description codes are designed for multiple path video streaming with channel diversities and an efficient MDC technique based on the applied spatial domain processing features. In this paper, we investigate the performance of multi-path video streaming using a multiple description coding (MDC) technique, especially the impacts of several codec variables, such as different lengths of the Group of Pictures (GOP), and the different startup times of I-frame in each independent MDC sub-streams. The overall performance of the system is evaluated by the frame dropout rate, which indicates the probability of playing back frozen frames of the reconstructed video at the receiver devices. To address dynamic channel conditions for video transmissions, we propose an adaptive coding technique by adjusting the GOP lengths according to the channel condition and combinatorial mathematics optimization in length of GOP adjustment. Different approaches, such as sub-dividing GOPs for a single stream and multiple sub-streams, and an adaptive MDC video streaming system, are examined in this paper.

Hierarchical Coding Structure for Video Coding and its Applicability in Scalable Video Coding

With the advancement in the video compression and internet technology, the application of video streaming has increased. Because of different types of devices used for accessing the video application and the heterogeneous nature of the network the scalable video coding has become important in order to fulfill the needs of the user. Discrete wavelet transform (DWT) is best tool for scalable video coding because of its property of multiresolution. The coding and display order of pictures in H.264/MPEG4-AVC is completely decoupled and any picture can be marked as reference picture and is used for prediction of following picture independent of corresponding slice type. A wavelet based hierarchical coding structure has been proposed which selects best matched reference frame for the current frame to be encoded based on the mean square error (MSE) in the group of picture(GOP). The scalable encoding of hierarchical prediction has also been exploited. This algorithm has been compared with the performance of traditional multiresolution motion estimation technique based on peak signal to noise ratio. The proposed algorithm show an improvement of 13% in PSNR value over the traditional MRME technique.

Unequal Loss Protection for H.264/AVC Video Streaming Over Wireless Networks

An efficient unequal loss protection (ULP) scheme for robust delivery of pre-encoded video with data partitioning over packet-lossy wireless networks is presented. The proposed scheme employs forward error correction (FEC) across packets to cope with the unreliable situations of the channel. To optimally allocate FEC codes for the different partitions packets of the different frames in one group of pictures (GOP), the overall expected distortion over one GOP is developed as the performance metric to guide the optimization process. In addition, a low-complexity FEC allocation algorithm is also proposed. Experimental results demonstrate that, compared with the other loss protection schemes, the proposed scheme achieves better reconstructed video quality.

Blind configuration of multi-view video coder prediction structure

Efficient coding of 3D multi-view video depends on the group of pictures (GOP) prediction structure and the video stream encoding order. Optimizing the GOP prediction structure and the stream coding order will reduce the coding bit rate, improve the peak signal to noise ratio (PSNR) and reduce the coding complexity. To date, conventional coders are manually configured based on prior knowledge of the geometric arrangement of the video cameras and the properties of the video streams. In this paper, a blind self-configurable multi-view video coder (BC-MVC) algorithm is introduced. The proposed BC-MVC blindly estimates a GOP prediction structure without prior knowledge of the cameras' geometric arrangement. The BC-MVC decomposes the key video frames into independent bases and a projection (mixing) matrix using blind source separation. Based on the mixing matrix, an algorithm is developed to estimate the cameras' geometric arrangement and consequently an optimum GOP prediction structure. The experimental results show that the proposed blind multi-view video coder has better coding efficiency than conventional 3D multi-view video coders with predefined coding structures. It also shows that BC-MVC is robust to camera failures and severe channel errors. Moreover, the numerical complexity analysis shows that the proposed BC-MVC algorithm has lower computational complexity than existing multi-view video prediction schemes.

Video coding with dynamic background

Motion estimation (ME) and motion compensation (MC) using variable block size, sub-pixel search, and multiple reference frames (MRFs) are the major reasons for improved coding performance of the H.264 video coding standard over other contemporary coding standards. The concept of MRFs is suitable for repetitive motion, uncovered background, non-integer pixel displacement, lighting change, etc. The requirement of index codes of the reference frames, computational time in ME & MC, and memory buffer for coded frames limits the number of reference frames used in practical applications. In typical video sequences, the previous frame is used as a reference frame with 68–92% of cases. In this article, we propose a new video coding method using a reference frame [i.e., the most common frame in scene (McFIS)] generated by dynamic background modeling. McFIS is more effective in terms of rate-distortion and computational time performance compared to the MRFs techniques. It has also inherent capability of scene change detection (SCD) for adaptive group of picture (GOP) size determination. As a result, we integrate SCD (for GOP determination) with reference frame generation. The experimental results show that the proposed coding scheme outperforms the H.264 video coding with five reference frames and the two relevant state-of-the-art algorithms by 0.5–2.0 dB with less computational time.

An Adaptive Rate Control Initialization Method for H.264 at Low Bit Rate

This paper presents an adaptive rate control initialization algorithm for H.264 at low bit rate. First we search the best initialization quantization parameters that used to generate a reconstructed video sequence with highest quality and reconstructed video sequence quality without extremely change of GOP (Group of Pictures) in different characteristic video sequence and different low bit rate. And then we propose a model to express the relationship of bit rate and best initialization quantization parameter. Moreover we use the proposed model to easily determine the best initialization quantization parameter of target bit rate. Compared with two noted algorithms, the measurement result of the objective PSNR and the subjective image quality of the proposed method has the best initialization quantization parameter.

Play-Out Constrained Dynamic Packet Loss Protection for Scalable Video Transmission

This paper analyzes the conventional unequal erasure protection (UXP) scheme for scalable video transmission, and proposes a dynamic hybrid UXP/ARQ transmission framework to improve the performance of the conventional UXP method for bandwidth-constrained scalable video transmission. This framework applies automatic retransmission request (ARQ) to the conventional UXP scheme for scalable video transmission, and dynamically adjusts the transmission time budget of each group of picture (GOP) according to the feedback about the transmission results of the current and previous GOPs from the receiver. Moreover, the parameter of target video quality is introduced and optimized to adapt to the channel condition in pursuit of more efficient dynamic time allocation. In addition, considering the play-out deadline constraint, the time schedule for the proposed scalable video transmission system is presented. Simulation results show that compared with the conventional UXP scheme and its enhanced method, the average peak signal to noise ratio (PSNR) of the reconstructed video can be improved significantly over a wide range of packet loss rates. Besides, the visual quality fluctuation among the GOPs can be reduced for the video which has much movement change.

An Adaptive Layered Hybrid ARQ Scheme for Scalable Video Transmission

 Abstract—In this paper, an adaptive layered hybrid ARQ scheme for scalable video transmission is proposed. The layered hybrid ARQ scheme is performed based on group of pictures (GOP). The sender dynamically adjusts the transmission decisions according to the feedback of transmission results and the channel condition. Meanwhile, the transmission time management is also adopted. The earliest start time and the latest end time of transmission procedure for each GOP are introduced to limit the buffer size and control the transmission delay. Simulation results show that the proposed scheme performs better than the conventional layered hybrid ARQ scheme in terms of average PSNR of reconstructed video in a wide range of packet loss rate over bandwidth-constrained networks.

Fusion of Global and Local Motion Estimation for Distributed Video Coding

The quality of side information plays a key role in distributed video coding. In this paper, we propose a new approach that consists of combining global and local motion compensation at the decoder side. The parameters of the global motion are estimated at the encoder using scale invariant feature transform features. Those estimated parameters are sent to the decoder in order to generate a globally motion compensated side information. Conversely, a locally motion compensated side information is generated at the decoder based on motion-compensated temporal interpolation of neighboring reference frames. Moreover, an improved fusion of global and local side information during the decoding process is achieved using the partially decoded Wyner-Ziv frame and decoded reference frames. The proposed technique improves significantly the quality of the side information, especially for sequences containing high global motion. Experimental results show that, as far as the rate-distortion performance is concerned, the proposed approach can achieve a PSNR improvement of up to 1.9 dB for a Group of Pictures (GOP) size of 2, and up to 4.65 dB for larger GOP sizes, with respect to the reference DISCOVER codec.

Impact of Compression on the Video Quality

This article deals with the impact of compression on the video quality. In the first part, a short characteristic of the most used MPEG compression standards is written. In the second part, the parameter Group of Picture (GOP) with particular I, P, B frames is explained. The third part focuses on the objective metrics which were used for evaluating the video quality. In the fourth part, the measurements and the experimental results are described.