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A distributed source autoencoder of local visual descriptors for 3D reconstruction

PATTERN RECOGNITION LETTERS 2021年 146卷 193-199页

作者： Milani, Simone Univ Padua Dept Informat Engn Via Gradenigo 6-B I-35131 Padua Italy

This paper presents a local descriptor coding scheme for multicamera surveillance and 3D reconstruction embedding an autoencoder into a traditional distributed source coding strategy. The proposed solution permits shifting most of the computational complexity at the decoder/receiver and exploiting the correlation among descriptors of different cameras (thus reducing the coded bit rate) without increasing the inter-device communication load. Experimental results show that the proposed scheme permits obtaining a satisfying accuracy with respect to the most recent solutions while generating a limited bit rate. (c) 2021 Elsevier B.V. All rights reserved.

关键词： distributed vision networks distributed source coding Autoencoder Local descriptor coding Structure-from-Motion

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Robust Video Transmission With distributed source Coded Auxiliary Channel

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2009年第12期18卷 2695-2705页

作者： Wang, Jiajun Majumdar, Abhik Ramchandran, Kannan NVIDIA Corp Santa Clara CA 95051 USA Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94270 USA Ooyala Inc Mountain View CA 94040 USA

We propose a novel solution to the problem of robust, low-latency video transmission over lossy channels. Predictive video codecs, such as MPEG and H. 26x, are very susceptible to prediction mismatch between encoder and decoder or "drift" when there are packet losses. These mismatches lead to a significant degradation in the decoded quality. To address this problem, we propose an auxiliary codec system that sends additional information alongside an MPEG or H.26x compressed video stream to correct for errors in decoded frames and mitigate drift. The proposed system is based on the principles of distributed source coding and uses the (possibly erroneous) MPEG/H.26x decoder reconstruction as side information at the auxiliary decoder. The distributed source coding framework depends upon knowing the statistical dependency (or correlation) between the source and the side information. We propose a recursive algorithm to analytically track the correlation between the original source frame and the erroneous MPEG/H.26x decoded frame. Finally, we propose a rate-distortion optimization scheme to allocate the rate used by the auxiliary encoder among the encoding blocks within a video frame. We implement the proposed system and present extensive simulation results that demonstrate significant gains in performance both visually and objectively (on the order of 2 dB in PSNR over forward error correction based solutions and 1.5 dB in PSNR over intrarefresh based solutions for typical scenarios) under tight latency constraints.

关键词： distributed source coding error resilience low latency video transmission

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Operational Rate-Distortion Performance of Single-source and distributed Compressed Sensing

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IEEE TRANSACTIONS ON COMMUNICATIONS 2014年第6期62卷 2022-2033页

作者： Coluccia, Giulio Roumy, Aline Magli, Enrico Politecn Torino Dipartimento Elettron & Telecomunicaz I-10129 Turin Italy INRIA F-78153 Rennes France

We consider correlated and distributed sources without cooperation at the encoder. For these sources, we derive the best achievable performance in the rate-distortion sense of any distributed compressed sensing scheme, under the constraint of high-rate quantization. Moreover, under this model we derive a closed-form expression of the rate gain achieved by taking into account the correlation of the sources at the receiver and a closed-form expression of the average performance of the oracle receiver for independent and joint reconstruction. Finally, we show experimentally that the exploitation of the correlation between the sources performs close to optimal and that the only penalty is due to the missing knowledge of the sparsity support as in (non distributed) compressed sensing. Even if the derivation is performed in the large system regime, where signal and system parameters tend to infinity, numerical results show that the equations match simulations for parameter values of practical interest.

关键词： Compressed sensing distributed source coding rate-distortion function Slepian-Wolf coding

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ADAE: ADVERSARIAL distributed source AUTOENCODER FOR POINT CLOUD COMPRESSION

ADAE: ADVERSARIAL DISTRIBUTED SOURCE AUTOENCODER FOR POINT C...

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IEEE International Conference on Image Processing (ICIP)

作者： Milani, Simone Univ Padova Dept Informat Engn Padua Italy

ISBN: (纸本)9781665441155

The current paper presents an adversarial autoencoding strategy for voxelized point cloud geometry based on the principles of distributed source coding. The encoder characterizes the input voxel blocks with an array of hash bytes while the decoder combines them with side information blocks in order to reconstruct the original data. The reconstruction process is optimized by classifying the reconstructed block with an adversarial discriminator in order to make the recovered data as close as possible to an original block. Experimental results show that the proposed solution generalizes well while obtaining better coding performance with respect to other state-of-the-art solutions and allowing high flexibility in rate shaping and decoding operations.

关键词： point cloud compression adversarial autoencoder distributed source coding decoding loss

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Theory and practice of rate division in distributed Video coding

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2008年第7期E91A卷 1806-1811页

作者： Wang, Peng Wang, Jia Yu, Songyu Pang, Yuye Shanghai Jiao Tong Univ Inst Image Commun & Informat Proc Dept Elect Engn Shanghai Peoples R China Shanghai Jiao Tong Univ Shanghai Key Lab Digital Media Proc & Transmiss Shanghai Peoples R China

Wyner and Ziv characterized the rate distortion function for lossy source coding with side information at the decoder. It is well known that for the quadratic Gaussian case, the Wyner-Ziv rate-distortion function coincides with the conditional rate-distortion function. In this paper, we extend the problem to the coding of multivariate Gaussian source with multiple Gaussian side information at the decoder. The achievable region is obtained, and it is easily extended to the case that the difference between the source and the side information is multivariate Gaussian, no matter what distributions the source and the side information are. We apply this theoretical model to distributed Video coding (DVC) by considering the difference of the distributed frame (D frame) and the Side-information frame (S frame) to be multivariate Gaussian distributed. This introduces rate allocation problem into DVC, which can be solved by a reverse water-filling method. Simulation results show that around 1.5-2 dB coding gain benefits from the multivariate Gaussian Wyner-Ziv coding model.

关键词： distributed source coding distributed video coding side-information frame distributed frame

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Dynamic Compression-Transmission for Energy-Harvesting Multihop Networks With Correlated sources

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IEEE-ACM TRANSACTIONS ON NETWORKING 2014年第6期22卷 1729-1741页

作者： Tapparello, Cristiano Simeone, Osvaldo Rossi, Michele Univ Padua Dept Informat Engn I-35131 Padua Italy NJIT CWCSPR Newark NJ 07102 USA

Energy-harvesting wireless sensor networking is an emerging technology with applications to various fields such as environmental and structural health monitoring. A distinguishing feature of wireless sensors is the need to perform both source coding tasks, such as measurement and compression, and transmission tasks. It is known that the overall energy consumption for source coding is generally comparable to that of transmission, and that a joint design of the two classes of tasks can lead to relevant performance gains. Moreover, the efficiency of source coding in a sensor network can be potentially improved via distributed techniques by leveraging the fact that signals measured by different nodes are correlated. In this paper, a data-gathering protocol for multihop wireless sensor networks with energy-harvesting capabilities is studied whereby the sources measured by the sensors are correlated. Both the energy consumptions of source coding and transmission are modeled, and distributed source coding is assumed. The problem of dynamically and jointly optimizing the source coding and transmission strategies is formulated for time-varying channels and sources. The problem consists in the minimization of a cost function of the distortions in the source reconstructions at the sink under queue stability constraints. By adopting perturbation-based Lyapunov techniques, a close-to-optimal online scheme is proposed that has an explicit and controllable tradeoff between optimality gap and queue sizes. The role of side information available at the sink is also discussed under the assumption that acquiring the side information entails an energy cost.

关键词： Data gathering distributed source coding energy harvesting Lyapunov optimization wireless sensor networks

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Generalized Compute-Compress-and-Forward

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IEEE TRANSACTIONS ON INFORMATION THEORY 2019年第1期65卷 462-481页

作者： Cheng, Hai Yuan, Xiaojun Tan, Yihua ShanghaiTech Univ Sch Informat Sci & Technol Shanghai 201210 Peoples R China Univ Elect Sci & Technol China Ctr Intelligent Networking & Commun Natl Key Lab Sci & Technol Commun Chengdu 611731 Sichuan Peoples R China Chinese Univ Hong Kong Dept Informat Engn Hong Kong Peoples R China NetEase Inc Hangzhou 310000 Zhejiang Peoples R China

Compute-and-forward (CF) harnesses interference in wireless communications by exploiting structured coding. The key idea of CF is to compute integer combinations of code words from multiple source nodes, rather than to decode individual code words by treating others as noise. Compute-compress-and-forward (CCF) can further enhance the network performance by introducing compression operations at receivers. In this paper, we develop a more general compression framework, termed generalized CCF (GCCF), where the compression function involves the selection of message segments over finite fields. We show that GCCF achieves a broader compression rate region than CCF. We also compare our compression rate region with the fundamental Slepian-Wolf (SW) region. We show that GCCF is optimal in the sense of achieving the minimum total compression rate. We also establish the criteria under which GCCF achieves the SW region. In addition, we consider a two-hop relay network employing the GCCF scheme. We formulate a sum-rate maximization problem and develop an approximate algorithm to solve the problem. Numerical results are presented to demonstrate the performance superiority of GCCF over CCF and other schemes.

关键词： Compute-and-forward nested lattice codes compute-compress-and-forward distributed source coding

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Geometry-based distributed scene representation with omnidirectional vision sensors

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2008年第7期17卷 1033-1046页

作者： Tosic, Ivana Frossard, Pascal Ecole Polytech Fed Lausanne Signal Proc Lab LTS4 CH-1015 Lausanne Switzerland

This paper addresses the problem of efficient representation of scenes captured by distributed omnidirectional vision sensors. We propose a novel geometric model to describe the correlation between different views of a 3-D scene. We first approximate the camera images by sparse expansions over a dictionary of geometric atoms. Since the most important visual features are likely to be equivalently dominant in images from multiple cameras, we model the correlation between corresponding features in different views by local geometric transforms. For the particular case of omnidirectional images, we define the multiview transforms between corresponding features based on shape and epipolar geometry constraints. We apply this geometric framework in the design of a distributed coding scheme with side information, which builds an efficient representation of the scene without communication between cameras. The Wyner-Ziv encoder partitions the dictionary into cosets of dissimilar atoms with respect to shape and position in the image. The joint decoder then determines pairwise correspondences between atoms in the reference image and atoms in the cosets of the Wyner-Ziv image in order to identify the most likely atoms to decode under epipolar geometry constraints. Experiments demonstrate that the proposed method leads to reliable estimation of the geometric transforms between views. In particular, the distributed coding scheme offers similar rate-distortion performance as joint encoding at low bit rate and outperforms methods based on independent decoding of the different images.

关键词： distributed source coding multiview geometry omnidirectional vision sparse approximations 3-D scene representation

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The Infinite-Message Limit of Two-Terminal Interactive source coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2013年第7期59卷 4071-4094页

作者： Ma, Nan Ishwar, Prakash Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94709 USA Boston Univ Dept Elect & Comp Engn Boston MA 02215 USA

A two-terminal interactive function computation problem with alternating messages is studied within the framework of distributed block source coding theory. For any finite number of messages, a single-letter characterization of the sum-rate-distortion function was established in previous works using standard information-theoretic techniques. This, however, does not provide a satisfactory characterization of the infinite-message limit, which is a new, unexplored dimension for asymptotic analysis in distributed block source coding involving potentially an infinite number of infinitesimal-rate messages. In this paper, the infinite-message sum-rate-distortion function, viewed as a functional of the joint source distribution and the distortion levels, is characterized as the least element of a partially ordered family of functionals having certain convex-geometric properties. The new characterization does not involve evaluating the infinite-message limit of a finite-message sum-rate-distortion expression. This characterization leads to a family of lower bounds for the infinite-message sum-rate-distortion expression and a simple criterion to test the optimality of any achievable infinite-message sum-rate-distortion expression. The new convex-geometric characterization is used to develop an iterative algorithm for evaluating any finite-message sum-rate-distortion function. It is also used to construct the first examples which demonstrate that for lossy source reproduction, two messages can strictly improve the one-message Wyner-Ziv rate-distortion function settling an unresolved question from a 1985 paper. It is shown that a single backward message of arbitrarily small rate can lead to an arbitrarily large gain in the sum-rate.

关键词： Alternating convexification Boolean AND communication complexity distributed source coding function computation interactive coding Wyner-Ziv coding

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A graph-based framework for transmission of correlated sources over multiple-access channels

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IEEE TRANSACTIONS ON INFORMATION THEORY 2007年第12期53卷 4583-4604页

作者： Pradhan, S. Sandeep Choi, Suhan Ramchandran, Kannan Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA

In this paper, we consider a graph-based framework for transmission of correlated sources over multiple-access channels. It is well known that the separation approach is not optimal for this multiuser communication. Our objective in this work is to reintroduce modularity in this problem using a graph-based discrete interface and to minimize the performance loss as compared to the optimal joint source-channel coding scheme. The proposed framework envisages a transmission systems with two modules: a source-coding module and a channel-coding module. In the former module, the correlated sources are encoded distributively into correlated messages whose correlation structure can be associated with a bipartite graph. These correlated messages are then encoded by using correlated codewords and are reliably transmitted over the multiple-access channel in the latter module. This leads to performance gains in terms of enlarging the class of correlated sources that can be reliably transmitted over a multiple-access channel as compared to the conventional separation approach. We provide an information-theoretic characterization of 1) the rate of exponential growth (as a function of the number of channel uses) of the size of the bipartite graphs whose edges can be reliably transmitted over a multiuser channel and 2) the rate of exponential growth (as a function of the number of source samples) of the size of the bipartite graphs which can reliably represent a pair of correlated sources to be transmitted over a multiuser channel.

关键词： discrete interface distributed source coding multiple-access channels random graphs

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