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IEEE International Conference on multimedia & Expo Workshops (ICMEW)

作者： Bondi, Luca Baroffio, Luca Cesana, Matteo Redondi, Alessandro Tagliasacchi, Marco Politecn Milan Dipartimento Elettron Informaz & Bioingn Milan Italy

ISBN: (纸本)9781479970797

Local visual features extracted from multiple camera views are employed nowadays in several application scenarios, such as object recognition, disparity matching, image stitching and many others. In several cases, local features need to be transmitted or stored on resource-limited devices, thus calling for efficient coding techniques. While recent works have addressed the problem of efficiently compressing local features extracted from still images or video sequences, in this paper we propose and evaluate an architecture for coding features extracted from multiple, overlapping views. The proposed multi-view Feature coding architecture can be applied to either real-valued or binary features, and allows to obtain bitrate reductions in the order of 10-20% with respect to simulcast coding.

关键词： local visual features multi-view coding

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ERROR RESILIENCE TECHNIQUE FOR multi-view coding USING REDUNDANT DISPARITY VECTORS

ERROR RESILIENCE TECHNIQUE FOR MULTI-VIEW CODING USING REDUN...

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International Conference on multimedia and Expo

作者： Dissanayake, M. B. De Silva, D. V. S. X. Worrall, S. T. Fernando, W. A. C. Univ Surrey Fac Engn & Phys Sci Guildford GU2 7XH Surrey England

ISBN: (纸本)9781424474936

Research on error resilience in multi-view coding is currently receiving considerable interest. While there is a multitude of literature concerning error recovery in 2D video, due to the statistical difference in motion compensation among temporal frames and disparity compensation among view points, such methods are inadequate to cater to the requirements of multi-view video transmission. This paper addresses the above issue by transmission of redundant disparity vectors for error recovery purposes. The proposed system, which is implemented using the Joint Scalable Video Model (JSVM) codec and tested using a simulated Internet Protocol (IP) packet network environment, can be used along with a suitable error concealment scheme to provide robust multi-view video transmission. The experimental results suggest that the proposed algorithm experiences a slight degradation of quality in error free environments due to the inclusion of redundant data. However, it improves the reconstructed picture quality significantly in error prone environments, specifically for Packet Loss Rates (PLRs) greater than 7%.

关键词： multi-view coding redundant coding error resilience

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multi-view images coding based on multiterminal source coding

Multi-view images coding based on multiterminal source codin...

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32nd IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Yang, Feng Dai, Qionghai Ding, Guiguang Tsinghua Univ Dept Automat Beijing 100084 Peoples R China

ISBN: (纸本)9781424407286

In this paper, we proposed a multi-view images coding method based on multiterminal Source coding (MSC). Due to separate encoding in MSC, our coding scheme can achieve good random access performance and the spatial redundancy can be exploited even if the encoders can not communicate with each other. Because of joint decoding, the compression performance of our scheme is promising, far better than that of separate encoding and decoding scheme. Compared to multi-view coding based on Wyner Ziv coding, our coding scheme is more flexible and can be easily extended to N views coding. There is no need to classify the view images into key images and Wyner Ziv images, images can be compressed in the same way and we can easily change the compression rate of each view to adapt to the resource conditions, like network bandwidth or storage. Experiment results show that the compression performance of our scheme is better than that of JPEG encoder and decoder scheme.

关键词： Wyner Ziv coding multiterminal source coding multi-view coding

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A Joint multi-view Plus Depth Image coding Scheme Based on 3D-Warping

A Joint Multi-View Plus Depth Image Coding Scheme Based on 3...

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1st ACM International Workshop on 3D Video Processing (3DVP)

作者： Zamarin, Marco Zanuttigh, Pietro Milani, Simone Cortelazzo, Guido M. Forchhammer, Soren Tech Univ Denmark Dept Photon Engn Lyngby Denmark Univ Padua I-35100 Padua Italy

ISBN: (纸本)9781450301596

Free viewpoint video applications and autostereoscopic displays require the transmission of multiple views of a scene together with depth maps. Current compression and transmission solutions just handle these two data streams as separate entities. However, depth maps contain key information on the scene structure that can be effectively exploited to improve the performance of multi-view coding schemes. In this paper we introduce a novel coding architecture that replaces the inter-view motion prediction operation with a 3D warping approach based on depth information to improve the coding performances. Ad-hoc solutions for occluded areas are also provided. Experimental results show that the proposed joint texture-depth compression approach is able to outperform the state-of-the-art H.264 MVC coding standard performances at low bit rates.

关键词： 3D image coding multi-view coding 3DTV warping image compression depth-based rendering

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multi-view DISTRIBUTED SOURCE coding OF BINARY FEATURES FOR VISUAL SENSOR NETWORKS 41

MULTI-VIEW DISTRIBUTED SOURCE CODING OF BINARY FEATURES FOR ...

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41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Monteiro, Nuno Brites, Catarina Pereira, Fernando Ascenso, Joao Inst Super Tecn Inst Telecomunicacoes Lisbon Portugal

ISBN: (纸本)9781479999880

Visual analysis algorithms have been mostly developed for a centralized scenario where all visual data is acquired and processed at a central location. However, in visual sensor networks (VSN), several constraints in computational power, energy and bandwidth require a radically different approach, notably a paradigm shift from centralized to distributed visual processing. In the new paradigm, visual data is acquired and features are extracted at the sensing nodes locations to be after transmitted to enable further analysis at some central location. In such scenario, one of the key challenges is to design suitable feature coding schemes that are able to exploit the correlation among the features corresponding to (partially) overlapped views of the same visual scene. To achieve efficient coding, it is proposed to employ the distributed source coding paradigm as it does not require any communication between the sensing nodes (rather expensive in VSN) and it is parsimonious in terms of computational resources. Experimental results show that significant accuracy and compression gains (up to 37.36%) can be achieved when coding features extracted from multiple views.

关键词： distributed source coding feature coding multi-view coding visual sensor networks

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Deep neural network based single pixel prediction for unified video coding

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NEUROCOMPUTING 2018年 272卷 558-570页

作者： Li, Honggui Trocan, Maria Yangzhou Univ Phys Coll Sci & Technol Yangzhou 225002 Jiangsu Peoples R China Inst Super Elect Paris Lab Informat Signal & Image Telecommun & Elect F-75006 Paris France

Classical video prediction methods exploit directly and shallowly the intra-frame, inter-frame and multi-view similarities within the video sequences;the proposed video prediction methods indirectly and intensively transform the frame correlations into nonlinear mappings by using a general deep neural network (DNN) with single output node. Traditional DNN based video prediction algorithms wholly and coarsely forecast the next frame, but the proposed video prediction algorithms severally and precisely anticipate single pixel of future frame in order to achieve high prediction accuracy and low computation cost. First of all, general DNN based prediction algorithms for intra-frame coding, inter-frame coding and multi-view coding are presented respectively. Then, general DNN based prediction algorithm for unified video coding is raised, which relies on the preceding three prediction algorithms. It is evaluated by simulation experiments that the proposed methods hold better performance than state of the art High Efficiency Video coding (HEVC) in peak signal to noise ratio (PSNR) and bit per pixel (BPP) in the situation of low bitrate transmission. It is also verified by experimental results that the proposed general DNN architecture possesses higher prediction accuracy and lower computation load than those of conventional DNN architectures. It is further testified by experimental results that the proposed methods are very suitable for multi-view videos with small correlations and big disparities. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Deep neural network Video prediction Unified video coding Intra-frame coding Inter-frame coding multi-view coding

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Channel Distortion Modeling for multi-view Video Transmission Over Packet-Switched Networks

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2011年第11期21卷 1679-1692页

作者： Zhou, Yuan Hou, Chunping Xiang, Wei Wu, Feng Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China Univ So Queensland Fac Engn & Surveying Toowoomba Qld 4350 Australia Microsoft Res Asia Beijing 100080 Peoples R China

Channel distortion modeling for generic multi-view video transmission remains a unfilled blank, despite that intensive research efforts have been devoted to model traditional 2-D video transmission. This paper aims to fill this blank through developing a recursive distortion model for multi-view video transmission over lossy packet-switched networks. Based on the study on the characteristics of multi-view video coding and the propagating behavior of transmission error due to random frame losses, a recursive mathematical model is derived to estimate the expected channel-induced distortion at both the frame and sequence levels. The model we develop explicitly considers both temporal and inter-view dependencies, induced by motion-compensated and disparity-compensated coding, respectively. The derived model is applicable to all multi-view video encoders using the classical block-based motion-/disparity-compensated prediction framework. Both objective and subjective experimental results are presented to demonstrate that the proposed model is capable of effectively model channel-induced distortion for multi-view video.

关键词： Distortion modeling multi-view coding multi-view video packet-switching networks video transmission

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An efficient rate-distortion optimization method for dependent view in MV-HEVC based on inter-view dependency

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2021年 94卷 116166-116166页

作者： Li, Tiansong Yu, Li Wang, Hongkui Kuang, Zhuo Huazhong Univ Sci & Technol Sch Elect Informat & Commun Wuhan 430074 Peoples R China

Rate?distortion optimization (RDO) is utilized to select the optimal coding parameters in multi-view video coding (MVC), which employs a Lagrange multiplier to balance the relationship between the distortion and the bitrate. In this paper, an efficient RDO method for the dependent view (DV) in multi-view video (MVV) is proposed based on inter-view dependency. First of all, by investigating the sources of the distortion in the DV, a new distortion model for the DV is established. In addition, based on the proposed distortion model, an efficient Lagrangian multiplier decision for B frame is proposed by considering the inter-view dependency. Finally, the optimized Lagrangian multiplier for P frame is designed using the scaling factor which is deduced to have a linear relationship with the disparity between I frame and P frame. Experiment results demonstrate that compared with the original HTM-16.0 encoder, the proposed overall method reduces 12.19% BD-rate for the DV on average, bringing 0.40 dB BD-PSNR gain.

关键词： RDO Inter-view dependency Lagrangian multiplier Dependent view multi-view coding

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1D representation of Isomap for united video coding

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multiMEDIA SYSTEMS 2018年第3期24卷 297-312页

作者： Li, Honggui Yangzhou Univ Phys Coll Sci & Technol 180 Siwangting Rd Yangzhou 225000 Jiangsu Peoples R China

This paper proposes a 1D representation of isometric feature mapping (Isomap) based united video coding algorithms. First, 1D Isomap representations that maintain distances are generated which can achieve a very high compression ratio. Next, embedding and reconstruction algorithms for the 1D Isomap representation are presented that can transform samples from a high-dimensional space to a low-dimensional space and vice versa. Then, dictionary learning algorithms for training samples are proposed to compress the input samples. Finally, a unified coding framework for diverse videos based on a 1D Isomap representation is built. The proposed methods make full use of correlations between internal and external videos, which are not considered by classical methods. Simulation experiments have shown that the proposed methods can obtain higher peak signal-to-noise ratios than standard highly efficient video coding for similar bit per pixel levels in the low bit rate situation.

关键词： 1D representation 1D coding Isomap Nonlinear dimensionality reduction multi-view coding Video coding

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Content Adaptive Enhancement of multi-view Depth Maps for Free viewpoint Video

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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2011年第2期5卷 352-361页

作者： Ekmekcioglu, Erhan Velisavljevic, Vladan Worrall, Stewart T. Univ Surrey I Lab Multimedia Commun Grp Ctr Vis Speech & Signal Proc Guildford GU2 7XH Surrey England Deutsch Telekom Labs D-10587 Berlin Germany

Depth map estimation is an important part of the multi-view video coding and virtual view synthesis within the free viewpoint video applications. However, computing an accurate depth map is a computationally complex process, which makes real-time implementation challenging. Alternatively, a simple estimation, though quick and promising for real-time processing, might result in inconsistent multi-view depth map sequences. To exploit this simplicity and to improve the quality of depth map estimation, we propose a novel content adaptive enhancement technique applied to the previously estimated multi-view depth map sequences. The enhancement method is locally adapted to edges, motion and depth-range of the scene to avoid blurring the synthesized views and to reduce the computational complexity. At the same time, and very importantly, the method enforces consistency across the spatial, temporal and inter-view dimensions of the depth maps so that both the coding efficiency and the quality of the synthesized views are improved. We demonstrate these improvements in the experiments, where the enhancement method is applied to several multi-view test sequences and the obtained synthesized views are compared to the views synthesized using other methods in terms of both numerical and perceived visual quality.

关键词： Depth estimation free viewpoint video multi-view coding multi-view depth map

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