Distributed Video Coding is becoming more and more popular among the research community, because of its interesting theoretical contributions and because there are still many open problems waiting to be solved. This paper introduces the codec architecture and the associated tools adopted by DISCOVER (DIStributed COding for Video sERvices), a European project which has been devoted to the advancement of Distributed Video Coding for two years. Along with the general description and pointers to references with more detailed information, this paper also presents some of the results obtained with the DISCOVER codec. An extended performance analysis and the codec’s executable file are both publicly available on the project’s web site www.discoverdvc.org.

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The DISCOVER codec: Architecture, Techniques and Evaluation

Low-complexity video encoding has been applicable to several emerging applications. Recently, distributed video coding (DVC) has been proposed to reduce encoding complexity to the order of that for still image encoding. In addition, compressive sensing (CS) has been applicable to directly capture compressed image data efficiently. In this paper, by integrating the respective characteristics of DVC and CS, a distributed compressive video sensing (DCVS) framework is proposed to simultaneously capture and compress video data, where almost all computation burdens can be shifted to the decoder, resulting in a very low-complexity encoder. At the decoder, compressed video can be efficiently reconstructed using the modified GPSR (gradient projection for sparse reconstruction) algorithm. With the assistance of the proposed initialization and stopping criteria for GRSR, derived from statistical dependencies among successive video frames, our modified GPSR algorithm can terminate faster and reconstruct better video quality. The performance of our DCVS method is demonstrated via simulations to outperform three known CS reconstruction algorithms.

Distributed compressive video sensing

Internet of Things (IoT) systems cannot successfully realize the notion of ubiquitous connectivity of everything if they are not capable to truly include 'multimedia things'. However, the current research and development activities in the field do not mandate the features of multimedia objects, thus leaving a gap to benefit from multimedia content based services and applications. In this paper, we analyze this issue by contemplating the concept of IoT and drawing an inspiration towards the perspective vision of 'Internet of Multimedia Things' (IoMT). Therein, we introduce IoMT as a novel paradigm in which smart heterogeneous multimedia things can interact and cooperate with one another and with other things connected to the Internet to facilitate multimedia based services and applications that are globally available to the users. Some applications and use-cases for IoMT are presented to reflect the possibilities enabled by this new paradigm. An IoMT architecture is then presented which is segregated into four distinct stages; (i) multimedia sensing, (ii) reporting and addressability, (iii) multimedia-aware cloud, and (iv) multi-agent systems. Instead of proposing specific technical solutions for each individual stage of the presented architecture, we survey the already existing technologies, providing a synthesis for the realization of the vision of IoMT. Subsequently, various requirements and challenges as well as the feasibility of existing solutions for each stage of proposed IoMT architecture are comprehensively discussed.

Internet of multimedia things

This paper addresses the problem of optimal minimum mean-squared error reconstruction of quantised samples in Wyner-Ziv video coding systems. Closed-form expressions of the optimal reconstructed values are derived for a Laplacian correlation model. The method is used for both single and multiple side information scenarios (the latter is also referred to as multi-hypothesis Wyner-Ziv decoding). The efficiency of the proposed optimal reconstruction method is confirmed by rate-distortion performance results, showing significant decrease of the distortion of the decoded sequence, compared to simple reconstruction methods that have been employed so far.

Optimal Reconstruction in Wyner-Ziv Video Coding with Multiple Side Information

Recent developments in low-cost CMOS cameras have created the opportunity of bringing imaging capabilities to sensor networks. Various visual sensor platforms have been developed with the aim of integrating visual data to wireless sensor applications. The objective of this article is to survey current visual sensor platforms according to in-network processing and compression/coding techniques together with their targeted applications. Characteristics of these platforms such as level of integration, data processing hardware, energy dissipation, radios and operating systems are also explored and discussed.

A survey of visual sensor network platforms

Distributed Video Coding (DVC) is a new video coding paradigm based on two major Information Theory results: the Slepian-Wolf and Wyner-Ziv theorems. Recently, practical DVC solutions have been proposed with promising results; however, there is still a need to study in a more systematic way the set of application scenarios for which DVC may bring major advantages. This paper intends to contribute for the identification of the most DVC friendly application scenarios, highlighting the expected benefits and drawbacks for each studied scenario. This selection is based on a proposed methodology which involves the characterization and clustering of the applications according to their most relevant characteristics, and their matching with the main potential DVC benefits.

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Distributed video coding: Selecting the most promising application scenarios

Using Distributed Video Coding (DVC), the complex task of exploiting the source statistics can be moved from the encoder to the decoder. Such a DVC decoder needs side information to exploit the statistics. In common DVC codecs, the side information is obtained by interpolating the current frame from already decoded frames. This paper proposes an interpolation technique for the side information that uses motion compensation with sub-pel accuracy, and compares different interpolation filters for calculating the sub-pel values. Using a six tab Wiener filter, we observe a gain of up to 1.8 dB for the DVC coded frames.

Side information interpolation with sub-pel motion compensation for wyner-ziv decoder

In video coding standards like H.264 / MPEG-4 AVC, the encoder performs motion estimation in order to utilise temporal dependencies within a sequence. In addition to the rate of the residue, the encoder has to allocate bits for motion vectors required to compensate the motion at the decoder. This bit rate increases for smaller block sizes, since more motion vectors need to be transmitted. Therefore, motion compensation using dense motion vector field is not feasible for such an architecture. This paper proposes to estimate motion for coding of B frames at the decoder. Using this decoder-side motion estimation, the transmission of the motion vectors is not necessary and the bit rate is reduced. Furthermore, prediction quality is higher in many cases resulting in a coding gain of up to 1.7 dB at low bit rates and 0.2 dB at higher bit rates.

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Decoder-side block motion estimation for H.264 / MPEG-4 AVC based video coding

In this paper, we present 2-D direction-adaptive transforms for coding prediction residuals of video These Direction-Adaptive Residual Transforms (DART) are shown to be more effective than the traditional 2-D DCT when coding residual blocks that contain directional features After presenting the directional transform structures and improvements to their efficiency, we outline how they are used to code both Inter and Intra prediction residuals For Intra coding, we also demonstrate the relation between the prediction mode and the optimal DART orientation Experimental results exhibit up to 7% and 93% improvements in compression efficiency in JM 160 and JM-KTA 26r1 respectively, as compared to using only the conventional H264/AVC transform

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Sven Klomp

Papers

The DISCOVER codec: Architecture, Techniques and Evaluation

Distributed video coding: Selecting the most promising application scenarios

Side information interpolation with sub-pel motion compensation for wyner-ziv decoder

Decoder-side block motion estimation for H.264 / MPEG-4 AVC based video coding

Direction-adaptive transforms for coding prediction residuals