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In this paper, we propose a novel multiview video plus depth (MVD) codec that uses a depth-based prediction mode (DBPM) both for texture videos and the depth maps. We show that the proposed codec can provide up to 9.2%, 9.9%, and 6.7% bitrate savings over H.264/MVC (MVC) for coding MVD data, depth maps, and multiview videos, respectively. In addition, we present subjective test results that compare the perceptual video quality of stereo videos coded with the DBPM-enabled codec and MVC. We also show that a typical Lagrangian rate-distortion optimization is effective to successfully choose between the prediction modes available to the proposed encoder. We provide a complexity analysis for the proposed codec as well and show that the encoder complexity is comparable to MVC, while the decoder complexity is about twice of MVC. Finally, we analyze the effects of different encoder control parameters on the virtual view synthesis quality. Results show that video QP has the most influence on the synthesis quality, and there is a tradeoff between the depth map QP and resolution. Lower depth map resolutions yield more bitrate savings, whereas for similar bitrates higher resolution and higher QP depth maps achieve better view synthesis performance. [ABSTRACT FROM PUBLISHER]

High Efficiency Video Coding (HEVC), a new video coding standard currently being established, adopts a quadtree-based Coding Unit (CU) block partitioning structure that is flexible in adapting various texture characteristics of images. However, this causes a dramatic increase in computational complexity compared to previous video coding standards due to the necessity of finding the best CU partitions. In this paper, a fast CU splitting and pruning method is presented for HEVC intra coding, which allows for significant reduction in computational complexity with small degradations in rate-distortion (RD) performance. The proposed fast splitting and pruning method is performed in two complementary steps: 1) early CU split decision and 2) early CU pruning decision. For CU blocks, the early CU splitting and pruning tests are performed at each CU depth level according to a Bayes decision rule method based on low-complexity RD costs and full RD costs, respectively. The statistical parameters for the early CU split and pruning tests are periodically updated on the fly for each CU depth level to cope with varying signal characteristics. Experimental results show that our proposed fast CU splitting and pruning method reduces the computational complexity of the current HM to about 50% in encoding time with only 0.6% increases in BD rate. [ABSTRACT FROM PUBLISHER]

This paper presents a performance evaluation study of coding efficiency versus computational complexity for the forthcoming High Efficiency Video Coding (HEVC) standard. A thorough experimental investigation was carried out to identify the tools that most affect the encoding efficiency and computational complexity of the HEVC encoder. A set of 16 different encoding configurations was created to investigate the impact of each tool, varying the encoding parameter set and comparing the results with a baseline encoder. This paper shows that, even though the computational complexity increases monotonically from the baseline to the most complex configuration, the encoding efficiency saturates at some point. Moreover, the results of this paper provide relevant information for implementation of complexity-constrained encoders by taking into account the tradeoff between complexity and coding efficiency. It is shown that low-complexity encoding configurations, defined by careful selection of coding tools, achieve coding efficiency comparable to that of high-complexity configurations. [ABSTRACT FROM PUBLISHER]

Distributed video coding (DVC) is a video coding paradigm that allows for a low-complexity encoding process by exploiting the temporal redundancies in a video sequence at the decoder side. State-of-the-art DVC systems exhibit a structural coding delay since exploiting the temporal redundancies through motion-compensated interpolation requires the frames to be decoded out of order. To alleviate this problem, we propose a system based on motion-compensated extrapolation that allows for efficient low-delay video coding with low complexity at the encoder. The proposed extrapolation technique first estimates the motion field between the two most recently decoded frames using the Lucas–Kanade algorithm. The obtained motion field is then extrapolated to the current frame using an extrapolation grid. The proposed techniques are implemented into a novel architecture featuring hybrid block-frequency Wyner–Ziv coding as well as mode decision. Results show that having references from both temporal directions in interpolation provides superior rate-distortion performance over a single temporal direction in extrapolation, as expected. However, the proposed extrapolation method is particularly suitable for low-delay coding as it performs better than H.264/AVC intra, and it is even able to outperform the interpolation-based DVC codec from DISCOVER for several sequences. [ABSTRACT FROM PUBLISHER]

This paper presents a real-time HD1080p view synthesis engine based on the reference algorithm from 3-D video coding team by solving high computational complexity and high memory cost problems. For the computational complexity, we propose the bilinear interpolation to simplify the hole filling process, and the Z scaling method with floating-point format to reduce the cost of homography calculation. For the memory cost, we propose the frame-level pipelining to reduce the requirement of warped depth maps, and the column-order warping method to remove the Z-buffer in occlusion handling. With the 90 nm complementary metal-oxide-semiconductor technology, our view synthesis engine can archive the throughput of 32.4 f/s for HD1080p videos with the gate count of 268.5 K and the internal memory of 69.4 kbytes. The experimental result shows our implementation has the similar synthesis quality as the original reference algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel variable bit rate (VBR) controller for real-time H.264/scalable video coding (SVC) applications. The proposed VBR controller relies on the fact that consecutive pictures within the same scene often exhibit similar degrees of complexity, and consequently should be encoded using similar quantization parameter (QP) values for the sake of quality consistency. In order to prevent unnecessary QP fluctuations, the proposed VBR controller allows for just an incremental variation of QP with respect to that of the previous picture, focusing on the design of an effective method for estimating this QP variation. The implementation in H.264/SVC requires to locate a rate controller at each dependency layer (spatial or coarse grain scalability). In particular, the QP increment estimation at each layer is computed by means of a radial basis function (RBF) network that is specially designed for this purpose. Furthermore, the RBF network design process was conceived to provide an effective solution for a wide range of practical real-time VBR applications for scalable video content delivery. In order to assess the proposed VBR controller, two real-time application scenarios were simulated: mobile live streaming and Internet protocol television broadcast. It was compared to constant QP encoding and a recently proposed constant bit rate (CBR) controller for H.264/SVC. The experimental results show that the proposed method achieves remarkably consistent quality, outperforming the reference CBR controller in the two scenarios for all the spatio-temporal resolutions considered. [ABSTRACT FROM AUTHOR]

Since different regions of a color image generally exhibit different spectral characteristics, the energy compaction of applying a single spectral transform to all regions is largely inefficient from a compression perspective. Thus, it is proposed that different subsets of wavelet coefficients of a color image be subjected to different spectral transforms before the resultant coefficients are coded by an efficient wavelet coefficient coding scheme such as that used in JPEG2000 or color set partitioning in hierarchical trees (CSPIHT). A quadtree represents the spatial partitioning of the set of high frequency coefficients of the color planes into spatially oriented subsets which may be further partitioned into smaller directionally oriented subsets. The partitioning decisions and decisions to employ fixed or signal-dependent bases for each subset are rate-distortion (R-D) optimized by employing a known analytical R-D model for these coefficient coding schemes. A compression system of asymmetric complexity, that integrates the proposed adaptive spectral transform with the CSPIHT coefficient coding scheme yields average coding gains of 0.3 dB and 0.9 dB in the Y component at 1.0 b/p and 2.5 b/p, respectively, and 0.9 dB and 1.35 dB in the U and V components at 1.0 b/p and 2.5 b/p, respectively, over a reference compression system that integrates the single spectral transform derived from the entire image with the CSPIHT coefficient coding scheme. [ABSTRACT FROM AUTHOR]

This paper jointly considers the mechanisms of rate control and the rate-distortion optimization (RDO) for the H.264/AVC hardware encoder. The proposed architecture performs intra prediction and inter prediction with our rate control mechanism in the first two stages. In addition, a low complexity macroblock (MB)-level mean absolute difference (MAD) prediction algorithm which considers both the motion information and the MAD value in the neighboring and current MBs is proposed. The proposed rate control algorithm can reduce the computational complexity and does not suffer from data dependency problems which may decrease the rate-distortion performance, thus it is suitable for H.264/AVC hardware encoders. Furthermore, the RDO-based architecture for the H.264/AVC encoder reduces the number of accurate rate-distortion cost calculators while maintaining the high rate-distortion performance. Experimental results show that the proposed rate control algorithm with the RDO-based architecture can improve the rate-distortion performance of H.264/AVC. [ABSTRACT FROM AUTHOR]

This letter investigates source-channel coding for error-resilient video streaming using redundant encoding. We estimate the end-to-end distortion per redundantly encoded macroblock (MB) via extension of the recursive optimal per-pixel estimate to encompass redundant transmissions. Redundant encoding is formulated as joint optimization of the MB parameters in the primary and redundant transmissions. We present three encoding strategies with different gain-complexity tradeoffs. The proposed methods are general in nature, and could be implemented on top of any (hybrid) video codec. Simulation results employing H.264's redundant slice mechanism show significant performance gains over conventional error-resilient encoding methods and naive redundant encoding schemes. [ABSTRACT FROM PUBLISHER]

In this paper, a novel algorithm called spatially varying transform (SVT) is proposed to improve the coding efficiency of video coders. SVT enables video coders to vary the position of the transform block, unlike state-of-art video codecs where the position of the transform block is fixed. In addition to changing the position of the transform block, the size of the transform can also be varied within the SVT framework, to better localize the prediction error so that the underlying correlations are better exploited. It is shown in this paper that by varying the position of the transform block and its size, characteristics of prediction error are better localized, and the coding efficiency is thus improved. The proposed algorithm is implemented and studied in the H.264/AVC framework. We show that the proposed algorithm achieves 5.85% bitrate reduction compared to H.264/AVC on average over a wide range of test set. Gains become more significant at medium to high bitrates for most tested sequences and the bitrate reduction may reach 13.50%, which makes the proposed algorithm very suitable for future video coding solutions focusing on high fidelity video applications. The gain in coding efficiency is achieved with a similar decoding complexity which makes the proposed algorithm easy to be incorporated in video codecs. However, the encoding complexity of SVT can be relatively high because of the need to perform a number of rate distortion optimization (RDO) steps to select the best location parameter (LP), which indicates the position of the transform. In this paper, a novel low complexity algorithm is also proposed, operating on a macroblock and a block level, to reduce the encoding complexity of SVT. Experimental results show that the proposed low complexity algorithm can reduce the number of LPs to be tested in RDO by about 80% with only a marginal penalty in the coding efficiency. [ABSTRACT FROM AUTHOR]

To achieve superior performance, rate-distortion optimized motion estimation (ME) for variable block size (RDO-VBSME) is often used in state-of-the-art video coding systems such as the H.264 JM software. However, the complexity of RDO-VBSME is very high both for software and hardware implementations. In this paper, we propose a hardware-friendly ME algorithm called RDOMFS with a novel hardware-friendly rate-distortion (RD)-like cost function, and a hardware-friendly modified motion vector predictor. Simulation results suggest that the proposed RDOMFS can achieve essentially the same RD performance as RDO-VBSME in JM. We also propose a matching hardware architecture with a novel Smart Snake Scanning order which can achieve very high data re-use ratio and data throughout. It is also reconfigurable because it can achieve variable data re-use ratio and can process variable frame size. The design is implemented with TSMC 0.18 \mum CMOS technology and costs 103 k gates. At a clock frequency of 63 MHz, the architecture achieves real-time 1920\,\times\,1080 RDO-VBSME at 30 frames/s. At a maximum clock frequency of 250 MHz, it can process 4096\,\times\,2160 at 30 frames/s. [ABSTRACT FROM AUTHOR]

Motion estimation (ME) is one of the most time-consuming parts in video coding. The use of multiple partition sizes in H.264/AVC makes it even more complicated when compared to ME in conventional video coding standards. It is important to develop fast and effective sub-pixel ME algorithms since: 1) the computation overhead by sub-pixel ME has become relatively significant while the complexity of integer-pixel search has been greatly reduced by fast algorithms, and 2) reducing sub-pixel search points can greatly save the computation for sub-pixel interpolation. In this letter, a novel fast sub-pixel ME algorithm is proposed which performs a “rough” sub-pixel search before the partition selection, and performs a “precise” sub-pixel search for the best partition. By reducing the searching load for the large number of non-best partitions, the computation complexity for sub-pixel search can be greatly decreased. Experimental results show that our method can reduce the sub-pixel search points by more than 50% compared to existing fast sub-pixel ME methods with negligible quality degradation. [ABSTRACT FROM AUTHOR]

This paper proposes a motion estimation scheme to reduce the computational complexity of multilayer motion estimation for scalable video coding. Based on the result of the motion estimation of the lower resolution layer referred to as base layer, we developed a new approach for exploring the search range of the enhancement layer with high coding efficiency. This approach is based on the activity defined as the absolute difference between the motion vector predictor and the final motion vector. Based on the correlation of the activities between neighboring layers, an inter-layer activity model was developed using a curve-fitted linear equation to exploit the activity in the base layer for deciding the search center and the search range of the enhancement layer. Each activity pair in the neighboring layers is used to associate the relevant macroblock to one of two groups; boundary region and interior region. The base-layer motion vector predictor is basically selected over all the activity regions; for each activity region, the proposed motion estimation algorithm decides whether to include the median motion vector predictor or not. Minimal sufficient search range is also decided from the inter-layer activity prediction factor that is adjusted to the given sequence. The proposed scheme reduced the execution time of motion estimation by 99.26% at the cost of 1.56% bit-rate increase and 0.048 dB peak signal-to-noise ratio (PSNR) decrease on average compared with the conventional full-search algorithm. The fast full-search block matching algorithm can also be incorporated to obtain the extra CPU time reduction in the motion estimation process. By adopting the fast full-search block matching algorithm (FFSBMA) in JSVM reference software, the CPU time was reduced by up to 91.84% and the memory bandwidth was reduced by 90% at the sacrifice of 1.27% bit-rate increase and 0.041 dB PSNR decrease on average compared with the FFSBMA only. [ABSTRACT FROM PUBLISHER]

A new object-based coding system for a class of dynamic image-based representations called plenoptic videos (PVs) is proposed. PVs are simplified dynamic light fields, where the videos are taken at regularly spaced locations along line segments instead of a 2-D plane. In the proposed object-based approach, objects at different depth values are segmented to improve the rendering quality. By encoding PVs at the object level, desirable functionalities such as scalability of contents, error resilience, and interactivity with an individual image-based rendering (IBR) object can be achieved. Besides supporting the coding of texture and binary shape maps for IBR objects with arbitrary shapes, the proposed system also supports the coding of grayscale alpha maps as well as depth maps (geometry information) to respectively facilitate the matting and rendering of the IBR objects. Both temporal and spatial redundancies among the streams in the PV are exploited to improve the coding performance, while avoiding excessive complexity in selective decoding of PVs to support fast rendering speed. Advanced spatial/temporal prediction methods such as global disparity-compensated prediction, as well as direct prediction and its extensions are developed. The bit allocation and rate control scheme employing a new convex optimization-based approach are also introduced. Experimental results show that considerable improvements in coding performance are obtained for both synthetic and real scenes, while supporting the stated object-based functionalities. [ABSTRACT FROM AUTHOR]

The newest video coding standard called scalable video coding (SVC) provides broad applications in multimedia communications. SVC encoder consumes great computational complexity when compared to previous video coding standards. This paper presents a fast mode decision algorithm that speeds up the SVC encoding process through probabilistic analysis. The mode of the enhancement layer is first predicted by statistical analysis. Afterward, Bayesian theorem is utilized to detect whether the prediction mode of the current macroblock is the best or not. The mode is further predicted and refined by the Markov process. Experimental results show that the proposed algorithm significantly reduces computational complexity with negligible peak signal-to-noise ratio degradation and bitrate increase in the enhancement layers. [ABSTRACT FROM AUTHOR]

A depth image-based error concealment algorithm for 3-D video transmission is proposed, which utilizes the strong correlations between 2-D video and its corresponding the depth map. We first investigate the internal characteristics of the macroblock in the depth map, and then take advantage of these characteristics to recover accurately the lost motion vector for the corrupted blocks, with the joint consideration of the neighbor information and the corresponding depth. Experimental results show that the proposed method provides significant improvements in terms of both objective and subjective evaluations. [ABSTRACT FROM AUTHOR]

In scalable video coding (SVC) as an extension of H.264/advanced video coding (AVC), a computationally expensive exhaustive mode decision is employed to select the best coding mode for each macroblock (MB). In order to reduce computational complexity, we propose a fast mode decision algorithm for SVC which uses an all-zero block (AZB) detection. Based on the empirical analysis of the inter-layer correlation of the AZB, the MB at the enhancement layer (EL) is predicted whether to be the AZB. Then, only predicted MBs are examined by the AZB detection algorithm. Since the mode decision can be terminated by detecting the AZB, we determine the processing order of the candidate modes at the EL in order to terminate the mode decision in the early stage. The proposed algorithm can be combined with other conventional fast mode decision methods in order to further reduce the computational complexity of those methods. Experimental results show that the proposed algorithm can significantly speed up the encoding process, especially for low bit-rate video sequences, without deteriorating the coding efficiency of SVC. [ABSTRACT FROM AUTHOR]

Wyner-Ziv (WZ) coding of video utilizes simple encoders and highly complex decoders. A transcoder from a WZ codec to a traditional codec can potentially increase the range of applications for WZ codecs. We present a transcoder scheme from the most popular WZ codec architecture to a differential pulse code modulation/discrete cosine transform codec. As a proof of concept, we implemented this transcoder using a simple pixeldomain WZ codec and the standard H.263+. The transcoder design aims at reducing complexity as a large amount of computation is saved by reusing the motion estimation, calculated at the side information generation process, and the I-frame streams. New approaches are used to generate side information and to map motion vectors for the transcoder. Results are presented to demonstrate the transcoder performance. [ABSTRACT FROM AUTHOR]

This paper explains the development of a highly efficient progressive 3-D mesh geometry coder based on the region adaptive transform in the spectral mesh compression method. A hierarchical set partitioning technique, originally proposed for the efficient compression of wavelet transform coefficients in high performance wavelet-based image coding methods, is proposed for the efficient compression of the coefficients of this transform. Experiments confirm that the proposed coder employing such a region adaptive transform has a high compression performance rarely achieved by other state of the art 3-D mesh geometry compression algorithms. A new, high-performance fixed spectral basis method is also proposed for reducing the computational complexity of the transform. Many-to-one mappings are employed to relate the coded irregular mesh region to a regular mesh whose basis is used. To prevent loss of compression performance due to the low-pass nature of such mappings, transitions are made from transform-based coding to spatial coding on a per region basis at high coding rates. Experimental results show the performance advantage of the newly proposed fixed spectral basis method over the original fixed spectral basis method in the literature that employs one-to-one mappings. [ABSTRACT FROM AUTHOR]

In scalable video coding (SVC), an exhaustive mode decision is performed to search for the best mode at each macroblock. Although this method achieves an optimal trade-off between rate and distortion, it introduces an extreme computational burden on the encoder. In this letter, we propose a fast mode decision algorithm that can reduce the computational load of the mode decision for SVC. We statistically derive the expectation of the rate-distortion cost (RDcost) increase caused by skipping each mode in the mode decision. In the proposed algorithm, the encoder performs the mode decision using a small number of modes that are determined based on the expected increase of the RDcost. Experimental results show that the proposed algorithm can reduce the computational complexity significantly with negligible video quality degradation and bitrate increment. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel 2-D layered multiple description coding (2DL-MDC) for error-resilient video transmission over unreliable networks. The proposed 2DL-MDC scheme allocates multiple description sub-bitstreams of a 2-D scalable bitstream to two network paths with unequal loss rates. We formulate the 2-D scalable rate-distortion problem and derive the expected distortion for the proposed scheme. To minimize the end-to-end distortion given the total rate budget and packet loss probabilities, we need to optimally allocate source and channel rates for each hierarchical sublayer of the scalable bitstream. The conventional Lagrangian multiplier method can be utilized to solve this problem but with overwhelming computational complexity. Therefore, we consider the use of the genetic algorithm to solve the rate-distortion optimization problem. The simulation results verify that the proposed method is able to achieve significant performance gain as opposed to the conventional equal rate allocation method. [ABSTRACT FROM AUTHOR]

Motion estimation (ME) plays an important role in modern video coders since it consumes approximately 60-80% of the entire encoder's computations. In this paper, three novel techniques are proposed to effectively speed up the ME process. First, a smart prediction technique for effectively deciding an initial search center is proposed. Second, a zero motion prejudgment technique is proposed to accurately decide whether the pre-estimated ISC can be considered as a best match motion vector (MV) and consequently save the required computations for the MV refinement process. Finally, a variable padding pixels ME technique is proposed to adaptively determine the number of padding pixels required for the search window for more computational cost savings. The three techniques are combined and applied to the block-based ME for a superior computational complexity savings in the ME process. The performance of the proposed techniques is tested in both the pixel domain ME and the frequency domain ME in terms of their quantitative visual quality (peak signal-to-noise ratio, PSNR), their computational complexity, and their bit rate. Experimental results demonstrate that the proposed fast ME technique is able to achieve approximately a 99.4% reduction in ME time compared to the conventional full search block-based ME (FSSBB-ME) with negligible degradation in both the PSNR and the bit rate. Additionally, the experimental results prove the effectiveness of the proposed techniques if they are combined with any blockbased ME technique such as the fast extended diamond enhanced predictive zonal search. Experimental results also demonstrate that there is at least an additional savings of 72% in ME time. using the conventional discrete cosine transform phase correlation ME (DCT-PC-ME) in the frequency domain compared to the conventional FSBB-ME technique in pixel domain. Compared to the conventional DCT-PC-ME, applying the proposed novel techniques to the DCT-PC-ME saves up to 89% in ME time. [ABSTRACT FROM AUTHOR]

This paper presents a bit-depth scalable coding solution that is compatible with the scalable extension of H.264/Advanced Video Coding (AVC), also referred to as scalable video coding (SVC). The proposed solution is capable of providing an 8-bit AVC main profile or high-profile base layer-coded bitstream multiplexed with a higher bit-depth-enhancement layer coded bitstream generated through macroblock level inter-layer bit-depth prediction. New decoding processes for inter-layer prediction are introduced to enable bit-depth scalability. Compatibility with other types of scalability in the SVC standard—temporal, spatial, and SNR scalability—is ensured. It also supports the single-loop decoding required in the SVC specification. Further- more, it supports adaptive inter-layer prediction to determine whether or not the inter-layer bit-depth prediction shall be invoked. This solution is implemented on the basis of the SVC reference software Joint Scalable Video Model version 8.12. Experimental results are presented on 8-bit to 10-bit bit-depth scalability and also combined bit-depth and spatial scalability. [ABSTRACT FROM AUTHOR]

Intra-mode and inter-mode predictions have been made available in H.264/AVC for effectively improving coding efficiency. However, exhaustively checking for all the prediction modes for identifying the best one (commonly referred to as exhaustive mode decision) greatly increases computational complexity. In this paper, a fast mode decision algorithm, called the motion activity-based mode decision (MAMD), is proposed to speed up the encoding process by reducing the number of modes required to be checked in a hierarchical manner, and is as follows. For each macroblock, the proposed MAMD algorithm always starts with checking the rate-distortion (RD) cost computed at the SKIP mode for a possible early termination, once the RD cost value is below a predetermined "low" threshold. On the other hand, if the RD cost exceeds another "high" threshold, then this indicates that only the intra modes are worthwhile to be checked. If the computed RD cost falls between the above-mentioned two thresholds, the remaining seven modes, which are classified into three motion activity classes in our work, will be examined, and only one of the three classes will be chosen for further mode checking. The above-mentioned motion activity can be quantitatively measured, which is equal to the maximum city- block length of the motion vector taken from a set of adjacent macroblocks (i.e., region of support, ROS). This measurement is then used to determine the most possible motion-activity class for the current macroblock. Experimental results have shown that, on average, the proposed MAMD algorithm reduces the computational complexity by 62.96%, while incurring only 0.059 dB loss in PSNR (peak signal-to-noise ratio) and 0.19% increment on the total bit rate compared to that of exhaustive mode decision, which is a default approach set in the JM reference software. [ABSTRACT FROM AUTHOR]

In this paper, a joint complexity-distortion optimization approach is proposed for real-time H.264 video encoding under the power-constrained environment. The power consumption is first translated to the encoding computation costs measured by the number of scaled computation units consumed by basic operations. The solved problem is then specified to be the allocation and utilization of the computational resources. A computation allocation model (CAM) with virtual computation buffers is proposed to optimally allocate the computational resources to each video frame. In particular, the proposed CAM and the traditional hypothetical reference decoder model have the same temporal phase in operations. Further, to fully utilize the allocated computational resources, complexity-configurable motion estimation (CAME) and complexity-configurable mode decision (CAMD) algorithms are proposed for H.264 video encoding. In particular, the CAME is performed to select the path of motion search at the frame level, and the CAMD is performed to select the order of mode search at the macroblock level. Based on the hierarchical adjusting approach, the adaptive allocation of computational resources and the fine scalability of complexity control can be achieved. [ABSTRACT FROM AUTHOR]

Video surveillance has been widely used in recent years to enhance public safety and privacy protection. A video surveillance system that deals with content analysis and activity monitoring needs efficient transmission and storage of the surveillance video data. Video compression techniques can be used to achieve this goal by reducing the size of the video with no or small quality loss. State-of-the-art video compression methods such as H.264/AVC often lead to high computational complexity at the encoder, which is generally implemented in a video camera in a surveillance system. This can significantly increase the cost of a surveillance system, especially when a mass deployment of end cameras is needed. In this paper, we discuss the specific considerations for surveillance video compression. We present a surveillance video compression system with low-complexity encoder based on Wyner-Ziv coding principles to address the tradeoff between computational complexity and coding efficiency. In addition, we propose a backward-channel aware Wyner-Ziv (BCAWZ) video coding approach to improve the coding efficiency while maintaining low complexity at the encoder. The experimental results show that for surveillance video contents, BCAWZ can achieve significantly higher coding efficiency than H.264/AVC INTRA coding as well as existing Wyner-Ziv video coding methods and is close to H.264/AVC INTER coding, while maintaining similar coding complexity with INTRA coding. This shows that the low motion characteristics of many surveillance video contents and the low-complexity encoding requirement make our scheme a particularly suitable candidate for surveillance video compression. We further propose an error resilience scheme for BCAWZ to address the concern of reliable transmission in the backward-channel, which is essential to the quality of video data for real-time and reliable object detection and event analysis. [ABSTRACT FROM AUTHOR]

The coding efficiency of a Wyner-Ziv video codec relies significantly on the quality of side information extracted at the decoder. The construction of efficient side information is difficult thanks in part to the fact that the original video sequence is not available at the decoder. Conventional motion search methods are widely used in the Wyner-Ziv video decoder to extract the side information. This substantially increases the Wyner-Ziv video decoding complexity. In this paper, we propose a new method to construct side estimation based on the idea of universal prediction. This method, referred to as Wyner-Ziv video coding with universal prediction (WZUP), does not perform motion search or assume an underlying model of the original input video sequences at the decoder. Instead, WZUP estimates the side information based on its observations on the past reconstructed video data. We show that WZUP can significantly reduce decoding complexity at the decoder and achieve a fair side estimation performance, thus making it possible to design both the video encoder and the decoder with low computational complexity. [ABSTRACT FROM AUTHOR]

A complexity reduction algorithm for an H.264 encoder is proposed. Computational savings are achieved by identifying, prior to motion estimation, macroblocks (MBs) that are likely to be skipped and hence saving further computational processing of these MBs. This early prediction is made by estimating a Lagrangian rate-distortion cost function which incorporates an adaptive model for the Lagrange multiplier parameter based on local sequence statistics. Simulation results demonstrate that the algorithm can achieve computational savings of 19%-67% (depending on the source sequence) with no significant loss of rate-distortion performance. [ABSTRACT FROM AUTHOR]

We analyze the problem of optimal data partitioning of MPEG-2 coded video in an operational rate-distortion context. The optimal algorithm is characterized and shown to have high complexity and delay. A causally optimal algorithm based on Lagrangian optimization is proposed, that optimally solves the problem for intra (I) pictures, and provides an optimal solution for predicted/interpolated (P/B) pictures when the additional constraints of causal operation and/or low-delay are imposed. A memoryless version of the algorithm, theoretically optimal for intrapictures only, is shown to perform almost identically but with significantly less computational complexity. Finally, a fast, suboptimal algorithm using purely rate-based optimization is also proposed, and is shown to perform quite close (within 1 dB) to the causally optimal one. Experimental results are provided using actual MPEG-2 coded video bitstreams. [ABSTRACT FROM AUTHOR]