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Circuits and Systems for Video Technology, IEEE Transactions on

Issue 5 • Date May 2012

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  • Table of contents

    Page(s): C1
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  • IEEE Transactions on Circuits and Systems for Video Technology publication information

    Page(s): C2
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  • Adaptive Correlation Estimation With Particle Filtering for Distributed Video Coding

    Page(s): 649 - 658
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (457 KB) |  | HTML iconHTML  

    Distributed video coding (DVC) is rapidly gaining popularity as a low cost, robust video coding solution, that reduces video encoding complexity. DVC is built on distributed source coding (DSC) principles where correlation between sources to be compressed is exploited at the decoder side. In the case of DVC, a current frame available only at the encoder is estimated at the decoder with side information generated from other frames available at the decoder. One of the main challenges in DVC design is that correlation among the source and side information needs to be estimated online and as accurately as possible. Since correlation dynamically changes with the scene, in order to exploit the robustness of DSC code designs, we integrate particle filtering (PF) with standard belief propagation (BP) decoding for inference on one joint factor graph to estimate correlation among source and side information. Correlation estimation is performed online as it is carried out jointly with decoding of the graph-based DSC code. Moreover, we demonstrate our joint bit-plane decoding with adaptive correlation estimation schemes within state-of-the-art DVC systems, which are transform-domain based with a feedback channel for rate adaptation. Experimental results show that our proposed system gives a significant performance improvement compared to the benchmark state-of-the-art DISCOVER codec (including correlation estimation) and the case without dynamic PF tracking, due to improved knowledge of timely correlation statistics via the combination of joint bit-plane decoding and particle-based BP (PBP) tracking. View full abstract»

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  • Adaptive Temporal Trajectory Filtering for Video Compression

    Page(s): 659 - 670
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (800 KB) |  | HTML iconHTML  

    Most in-loop filters currently being employed in video compression algorithms use spatial information from a single frame of the video sequence only. In this paper, a new filter is introduced and investigated that combines both spatial and temporal information to provide subjective and objective quality improvement. The filter only requires a small overhead on slice level while using the temporal information conveyed in the bit stream to reconstruct the individual motion trajectory of every pixel in a frame at both encoder and decoder. This information is then used to perform pixel-wise adaptive motion-compensated temporal filtering. It is shown that the filter performs better than the state-of-the-art codec H.264/AVC over a large range of sequences and bit rates. Additionally, the filter is compared with another, Wiener-based in-loop filtering approach and a complexity analysis of both algorithms is conducted. View full abstract»

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  • Modeling of Rate and Perceptual Quality of Compressed Video as Functions of Frame Rate and Quantization Stepsize and Its Applications

    Page(s): 671 - 682
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1324 KB) |  | HTML iconHTML  

    This paper first investigates the impact of frame rate and quantization on the bit rate and perceptual quality of compressed video. We propose a rate model and a quality model, both in terms of the quantization stepsize and frame rate. Both models are expressed as the product of separate functions of quantization stepsize and frame rate. The proposed models are analytically tractable, each requiring only a few content-dependent parameters. The rate model is validated over videos coded using both scalable and nonscalable encoders, under a variety of encoder settings. The quality model is validated only for a scalable video, although it is expected to be applicable to a single-layer video as well. We further investigate how to predict the model parameters using the content features extracted from original videos. Results show accurate bit rate and quality prediction (average Pearson correlation >;0.99) can be achieved with model parameters predicted using three features. Finally, we apply rate and quality models for rate-constrained scalable bitstream adaptation and frame rate adaptive rate control. Simulations show that our model-based solutions produce better video quality compared with conventional video adaptation and rate control. View full abstract»

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  • A Linear Dynamical System Framework for Salient Motion Detection

    Page(s): 683 - 692
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (448 KB) |  | HTML iconHTML  

    Detection of salient motion in a video involves determining which motion is attended to by the human visual system in the presence of background motion that consists of complex visuals that are constantly changing. Salient motion is marked by its predictability compared to the more complex unpredictable motion of the background such as fluttering of leaves, ripples in water, dispersion of smoke, and others. We introduce a novel approach to detect salient motion based on the concept of “observability” from the output pixels, when the video sequence is represented as a linear dynamical system. The group of output pixels with maximum saliency is further used to model the holistic dynamics of the salient region. The pixel saliency map is bolstered by two region-based saliency maps, which are computed based on the similarity of dynamics of the different spatiotemporal patches in the video with the salient region dynamics, in a global as well as a local sense. The resulting algorithm is tested on a set of challenging sequences and compared to state-of-the-art methods to showcase its superior performance on grounds of its computational efficiency and ability to detect salient motion. View full abstract»

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  • Improved Hand Tracking System

    Page(s): 693 - 701
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (913 KB) |  | HTML iconHTML  

    This paper presents an improved hand tracking system using pixel-based hierarchical-feature AdaBoosting (PBHFA), skin color segmentation, and codebook (CB) background cancellation. The proposed PBH feature significantly reduces the training time by a factor of at least 1440 compared to the traditional Haar-like feature. Moreover, lower computation and high tracking accuracy are also provided simultaneously. Yet, one of the disadvantages of the PBHFA is the false positive which is the consequence of the appearance of complex background in positive samples. To effectively reduce the false positive rate, the skin color segmentation and the foreground detection by applying the CB model are catered for rejecting all of the candidates which are not hand targets. As documented in the experimental results, the proposed system can achieve promising results, and thus it can be considered as an effective candidate in handling practical applications which require hand postures. View full abstract»

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  • Simplified Multitarget Tracking Using the PHD Filter for Microscopic Video Data

    Page(s): 702 - 713
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (451 KB) |  | HTML iconHTML  

    The probability hypothesis density (PHD) filter from the theory of random finite sets is a well-known method for multitarget tracking. We present the Gaussian mixture (GM) and improved sequential Monte Carlo implementations of the PHD filter for visual tracking. These implementations are shown to provide advantages over previous PHD filter implementations on visual data by removing complications such as clustering and data association and also having beneficial computational characteristics. The GM-PHD filter is deployed on microscopic visual data to extract trajectories of free-swimming bacteria in order to analyze their motion. Using this method, a significantly larger number of tracks are obtained than was previously possible. This permits calculation of reliable distributions for parameters of bacterial motion. The PHD filter output was tested by checking agreement with a careful manual analysis. A comparison between the PHD filter and alternative tracking methods was carried out using simulated data, demonstrating superior performance by the PHD filter in a range of realistic scenarios. View full abstract»

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  • Intracoding and Refresh With Compression-Oriented Video Epitomic Priors

    Page(s): 714 - 726
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1532 KB) |  | HTML iconHTML  

    In video compression, intracoding plays an important role in terms of coding efficiency and error resilience and has been an attractive research topic since the standardization of H.264/AVC. In this paper, we propose a high-performance intracoding scheme with the help of epitomic priors. Different from intracoding in H.264/AVC and other video standards, we construct image epitomes as coding priors and use them to generate predictions of intrablocks at the encoder. In addition, we losslessly code and transmit the image epitomes to the decoder. We perform compression-oriented video epitomic analysis and search for the best epitomic priors by using the expectation maximization algorithm. The resulting image epitomes for a video sequence can be viewed as the base layer in spatially scalable video coding. Experiments show that our proposed intracoding scheme improves the state of the art by an average of 0.53 dB in PSNR. Simulations under a packet loss environment also demonstrate that intrarefresh with epitomic priors outperforms random intrarefresh by up to 2 dB, leading to better subjective quality. View full abstract»

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  • Structural Solutions for Dynamic Scheduling in Wireless Multimedia Transmission

    Page(s): 727 - 739
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (497 KB) |  | HTML iconHTML  

    In this paper, we propose a systematic solution to the problem of scheduling delay-sensitive media data for transmission over time-varying wireless channels. We first formulate the dynamic scheduling problem as a Markov decision process that explicitly considers the users' heterogeneous multimedia data characteristics (e.g., delay deadlines, distortion impacts and dependences, and so on) and time-varying channel conditions, which are not simultaneously considered in state-of-the-art packet scheduling algorithms. This formulation allows us to perform foresighted decisions to schedule multiple data units for transmission at each time in order to optimize the long-term utilities of the multimedia applications. The heterogeneity of the media data enables us to express the transmission priorities between the different data units as a priority graph, which is a directed acyclic graph. This priority graph provides us with an elegant structure to decompose the multidata unit foresighted decision at each time into multiple single-data unit foresighted decisions which can be performed sequentially, from the high priority data units to the low priority data units, thereby significantly reducing the computation complexity. When the statistical knowledge of the multimedia data characteristics and channel conditions is unknown a priori, we develop a low-complexity online learning algorithm to update the value functions, which capture the impact of the current decision on the future utility. The simulation results show that the proposed solution significantly outperforms existing state-of-the-art scheduling solutions. View full abstract»

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  • Novel 2-D MMSE Subpixel-Based Image Down-Sampling

    Page(s): 740 - 753
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (932 KB) |  | HTML iconHTML  

    Subpixel-based down-sampling is a method that can potentially improve apparent resolution of a down-scaled image on LCD by controlling individual subpixels rather than pixels. However, the increased luminance resolution comes at price of chrominance distortion. A major challenge is to suppress color fringing artifacts while maintaining sharpness. We propose a new subpixel-based down-sampling pattern called diagonal direct subpixel-based down-sampling (DDSD) for which we design a 2-D image reconstruction model. Then, we formulate subpixel-based down-sampling as a MMSE problem and derive the optimal solution called minimum mean square error for subpixel-based down-sampling (MMSE-SD). Unfortunately, straightforward implementation of MMSE-SD is computational intensive. We thus prove that the solution is equivalent to a 2-D linear filter followed by DDSD, which is much simpler. We further reduce computational complexity using a small k × k filter to approximate the much larger MMSE-SD filter. To compare the performances of pixel and subpixel-based down-sampling methods, we propose two novel objective measures: normalized l1 high frequency energy for apparent luminance sharpness and PSNRU(V) for chrominance distortion. Simulation results show that both MMSE-SD and MMSE-SD(k) can give sharper images compared with conventional down-sampling methods, with little color fringing artifacts. View full abstract»

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  • A Multiple Description Video Codec With Adaptive Residual Distributed Coding

    Page(s): 754 - 768
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1932 KB) |  | HTML iconHTML  

    Multiple description coding (MDC) decomposes one single media into several descriptions and transmits them over different channels for error resilience. Each description contributes to improving the reconstructed media quality when decoded. Distributed video coding (DVC) encodes multiple correlated images and utilizes error correction codes to shift the codec complexity to a joint decoder. Combining MDC with DVC (MDVC) yields a stable codec for mobile encoders. In this paper, to improve the MDVC codec performance, image correlations among the MDVC processing modules were exploited to improve reconstructed video quality and enhance transmission robustness. At the side encoder, a DVC-based adaptive differential pulse code modulation was designed to remove interframe redundancy to enhance rate-distortion performances. For the MDVC central decoding, intradescription and interdescription correlations were utilized to dynamically select the best reconstructed frames from two descriptions, instead of selecting just one description or all key-frames from two descriptions. Experiments showed that, as compared to previous methods, the proposed MDVC control method yielded 1-2 dB higher in image PSNRs for Wyner-Ziv reconstructed frames at the side decoder when encoding low-to-medium complexity videos. For high-complexity videos, it effectively prevents error correction of Wyner-Ziv frames from malfunctioning and yields about 3 dB higher in PSNR. The proposed MDVC central decoder control yields 1-4 dB higher PSNRs, as compared to side decoders. Under lossy transmission, it demonstrates 27-64% smaller PSNR variations, as compared to that of combining key-frames as the decoded video. The proposed MDVC system and control not only improve the DVC reconstructed video quality, but also reduce the quality fluctuation artifacts of MDC coded video for mobile coders. View full abstract»

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  • Efficient Construction for Region Incrementing Visual Cryptography

    Page(s): 769 - 777
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (495 KB) |  | HTML iconHTML  

    A region incrementing visual cryptography scheme (RIVCS) deals with the sharing of an image consisting of multiple regions with different secrecy levels, which can be incrementally revealed as the number of shares increases. The encoding basis matrices of RIVCS for an image containing three to five regions have been reported in the literature, but no construction method has ever been studied. We develop a novel and efficient construction for RIVCS using linear programming in this paper. The proposed integer linear program aims at the minimization of the pixel expansion under the constraints for being a RIVCS. Experimental results demonstrate the feasibility, applicability, and flexibility of our construction. The pixel expansions and contrasts derived from our scheme are also better than the previous results. View full abstract»

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  • Understanding Compressive Sensing and Sparse Representation-Based Super-Resolution

    Page(s): 778 - 789
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1539 KB) |  | HTML iconHTML  

    Recently, compressive sensing (CS) has emerged as a powerful tool for solving a class of inverse/underdetermined problems in computer vision and image processing. In this paper, we investigate the application of CS paradigms on single image super-resolution (SR) problems that are considered to be the most challenging in this class. In light of recent promising results, we propose novel tools for analyzing sparse representation-based inverse problems using redundant dictionary basis. Further, we provide novel results establishing tighter correspondence between SR and CS. As such, we gain insights into questions concerning regularizing the solution to the underdetermined problem, such as follows. 1) Is sparsity prior alone sufficient? 2) What is a good dictionary? 3) What is the practical implication of noncompliance with theoretical CS hypothesis? Unlike in other underdetermined problems that assume random down-projections, the low-resolution image formation model employed in CS-based SR is a deterministic down-projection that may not necessarily satisfy some critical assumptions of CS. We further investigate the impact of such projections in concern to the above questions. View full abstract»

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  • Joint Complexity Estimation of I-Frame and P-Frame for H.264/AVC Rate Control

    Page(s): 790 - 798
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (596 KB) |  | HTML iconHTML  

    Rate control plays a significant role for high quality video coding. This paper presents a rate control method for H.264/AVC, using a new bit allocation scheme for both I-frame and P-frame. This scheme is based on our proposed frame complexity measurement and estimation model. The measurement model considers not only the absolute complexity of I-frame and P-frame, respectively, but also the complexity relationship between I-frame and P-frame. Our proposed bit allocation scheme is able to allocate bit rate more efficiently for both I-frame and P-frame in order to achieve a relatively steady visual quality. Experimental results show that our proposed method is capable of providing more stable video quality than other existing methods. View full abstract»

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  • k Out of n Region Incrementing Scheme in Visual Cryptography

    Page(s): 799 - 810
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (486 KB) |  | HTML iconHTML  

    Recently, Wang introduced a novel (2, n ) region incrementing visual cryptographic scheme (RIVCS), which can gradually reconstruct secrets in a single image with multiple security levels. In RIVCS, the secret image is subdivided into multiple regions in such a way that any t shadow images, where 2 ≤ tn, can be used to reveal the (t-1) th region. However, Wang's scheme suffers from the incorrect-color problem, which the colors of reconstructed images may be reversed (i.e., the black and white are reversed). If the color of text is also the secret information, the incorrect-color problem will compromise the secret. Additionally, Wang's scheme is only suitable for the 2-out-of-n case, i.e., (k,n)-RIVCS where k=2. In this paper, we propose a general (k,n)-RIVCS, where k and n are any integers, that is able to reveal correct colors of all regions. This paper has made three main contributions: 1) our scheme is a general (k,n)-RIVCS, where k and n can be any integers; 2) the incorrect-color problem is solved; and 3) our (k,n)-RIVCS is theoretically proven to satisfy the security and contrast conditions. View full abstract»

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  • Effect of Vergence–Accommodation Conflict and Parallax Difference on Binocular Fusion for Random Dot Stereogram

    Page(s): 811 - 816
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (545 KB) |  | HTML iconHTML  

    Recently, various studies of human factors have been conducted to reveal stereoscopic characteristics of the human visual system and visual fatigue. In this paper, we investigate the effect of vergence-accommodation conflict and parallax difference on binocular fusion for random dot stereograms. The aim of this paper is to provide a study on visual fatigue induced by the conflict. We measured the time required for fusion under various conditions that include foreground parallax, background parallax, focal distance, aperture size, and corrugation frequency. The results show that foreground parallax and parallax difference between foreground parallax and background parallax have significant influences on fusion time. In addition, we verify the relationship between fusion time and visual fatigue by conducting a subjective evaluation of stereoscopic images. View full abstract»

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  • IEEE Circuits and Systems Society Information

    Page(s): C3
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  • IEEE Transactions on Circuits and Systems for Video Technology information for authors

    Page(s): C4
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Aims & Scope

The emphasis is focused on, but not limited to:
1. Video A/D and D/ A
2. Video Compression Techniques and Signal Processing
3. Multi-Dimensional Filters and Transforms
4. High Speed Real-Tune Circuits
5. Multi-Processors Systems—Hardware and Software
6. VLSI Architecture and Implementation for Video Technology 

 

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dan Schonfeld
Multimedia Communications Laboratory
ECE Dept. (M/C 154)
University of Illinois at Chicago (UIC)
Chicago, IL 60607-7053
tcsvt-eic@tcad.polito.it

Managing Editor
Jaqueline Zelkowitz
tcsvt@tcad.polito.it