Compressed Sensing Based Low-Power Multi-View Video Coding and Transmission in Wireless Multi-Path Multi-Hop Networks

Wireless Multimedia Sensor Network (WMSN) is increasingly being deployed for surveillance, monitoring and Internet-of-Things (IoT) sensing applications where a set of cameras capture and compress local images and then transmit the data to a remote controller. Such captured local images may also be c...

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Published inIEEE transactions on mobile computing Vol. 21; no. 9; pp. 3122 - 3137
Main Authors Cen, Nan, Guan, Zhangyu, Melodia, Tommaso
Format Magazine Article
LanguageEnglish
Published Los Alamitos IEEE 01.09.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Coders
Coding
Compressed sensing
Computer architecture
Decoders
Decoding
Encoding
Image coding
Internet of Things
Mathematical problems
multi-view video streaming
Multimedia
network optimization
Performance evaluation
Power consumption
Redundancy
Remote control
Spread spectrum communication
Streaming media
Video compression
Video transmission
Wireless communication
Wireless networks
Wireless sensor networks
Online AccessGet full text
ISSN1536-1233
1558-0660
DOI10.1109/TMC.2021.3049797

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Abstract Wireless Multimedia Sensor Network (WMSN) is increasingly being deployed for surveillance, monitoring and Internet-of-Things (IoT) sensing applications where a set of cameras capture and compress local images and then transmit the data to a remote controller. Such captured local images may also be compressed in a multi-view fashion to reduce the redundancy among overlapping views. In this paper, we present a novel paradigm for compressed-sensing-enabled multi-view coding and streaming in WMSN. We first propose a new encoding and decoding architecture for multi-view video systems based on Compressed Sensing (CS) principles, composed of cooperative sparsity-aware block-level rate-adaptive encoders, feedback channels and independent decoders. The proposed architecture leverages the properties of CS to overcome many limitations of traditional encoding techniques, specifically massive storage requirements and high computational complexity. Then, we present a modeling framework that exploits the aforementioned coding architecture. The proposed mathematical problem minimizes the power consumption by jointly determining the encoding rate and multi-path rate allocation subject to distortion and energy constraints. Extensive performance evaluation results show that the proposed framework is able to transmit multi-view streams with guaranteed video quality at lower power consumption.
AbstractList Wireless Multimedia Sensor Network (WMSN) is increasingly being deployed for surveillance, monitoring and Internet-of-Things (IoT) sensing applications where a set of cameras capture and compress local images and then transmit the data to a remote controller. Such captured local images may also be compressed in a multi-view fashion to reduce the redundancy among overlapping views. In this paper, we present a novel paradigm for compressed-sensing-enabled multi-view coding and streaming in WMSN. We first propose a new encoding and decoding architecture for multi-view video systems based on Compressed Sensing (CS) principles, composed of cooperative sparsity-aware block-level rate-adaptive encoders, feedback channels and independent decoders. The proposed architecture leverages the properties of CS to overcome many limitations of traditional encoding techniques, specifically massive storage requirements and high computational complexity. Then, we present a modeling framework that exploits the aforementioned coding architecture. The proposed mathematical problem minimizes the power consumption by jointly determining the encoding rate and multi-path rate allocation subject to distortion and energy constraints. Extensive performance evaluation results show that the proposed framework is able to transmit multi-view streams with guaranteed video quality at lower power consumption.
Author Guan, Zhangyu
Melodia, Tommaso
Cen, Nan
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SubjectTerms Coders
Coding
Compressed sensing
Computer architecture
Decoders
Decoding
Encoding
Image coding
Internet of Things
Mathematical problems
multi-view video streaming
Multimedia
network optimization
Performance evaluation
Power consumption
Redundancy
Remote control
Spread spectrum communication
Streaming media
Video compression
Video transmission
Wireless communication
Wireless networks
Wireless sensor networks
Title Compressed Sensing Based Low-Power Multi-View Video Coding and Transmission in Wireless Multi-Path Multi-Hop Networks
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Volume 21
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