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A study on visual sensor network cross-layer resource allocation using quality-based criteria and metaheuristic optimization algorithms

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APPLIED SOFT COMPUTING 2015年 26卷 149-165页

作者： Pandremmenou, K. Kondi, L. P. Parsopoulos, K. E. Univ Ioannina Dept Comp Sci & Engn GR-45110 Ioannina Greece

visual sensor networks (VSNs) consist of spatially distributed video cameras that are capable of compressing and transmitting the video sequences they acquire. We consider a direct-sequence code division multiple access (DS-CDMA) VSN, where each node has its individual requirements in compression bit rate and energy consumption, depending on the corresponding application and the characteristics of the monitored scene. We study two optimization criteria for the optimal allocation of the source and channel coding rates, which assume discrete values, as well as for the power levels of all nodes, which are continuous, under transmission bit rate constraints. The first criterion minimizes the average distortion of the video received by all nodes, while the second one minimizes the maximum video distortion among all nodes. The resulting mixed integer optimization problems are tackled with a modern optimization algorithm, namely particle swarm optimization (PSO), as well as a hybrid scheme that combines PSO with the deterministic Active-Set optimization method. Extensive experimentation on interference-limited as well as noisy environments offers significant intuition regarding the effectiveness of the considered optimization schemes, indicating the impact of the video sequence characteristics on the joint determination of the transmission parameters of the VSN. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Hybrid algorithms Metaheuristic optimization Particle swarm optimization Power control Resource allocation visual sensor network

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Heterogeneous Feature Fusion-based Optimal Face Image Acquisition in visual sensor network

Heterogeneous Feature Fusion-based Optimal Face Image Acquis...

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32nd Annual IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

作者： Lin, Kuicheng Wang, Xue Cui, Sujin Tan, Yuqi Tsinghua Univ Dept Precis Instrument State Key Lab Precis Measurement Technol & Instru Beijing Peoples R China

ISBN: (纸本)9781479961139

High quality face image acquisition from huge video data obtained in visual sensor network is of great significance in applications related to face processing, such as face recognition and reconstruction. This paper proposes an optimal face image acquisition method in visual sensor network, which is based on collaborative face frames acquisition and heterogeneous feature fusion-based face quality assessment. Gaussian-probability-distribution-based multi-view data fusion and kalman filter are used for collaborative target localization and tracking. To achieve primary screening of face frames, a lightweight face frames quality evaluation method is presented. Importantly, new face quality assessment criterion calculation methods are proposed to make fine screening of face images more applicable in visual sensor network. The new face quality assessment criterion calculation methods are based on heterogeneous feature fusion of pedestrian tracking and static face image features analysis. Fuzzy inference engine is used to combine these criteria to generate a face quality assessment score. Experimental results show that the proposed method can acquire optimal face images accurately and robustly.

关键词： optimal face image acquisition fuzzy inference engine visual sensor network face quality assessment

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A visual sensor network for Parking Lot Occupancy Detection in Smart Cities 2

A Visual Sensor Network for Parking Lot Occupancy Detection ...

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2015 IEEE 2nd World Forum on Internet of Things (WF-IoT)

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

ISBN: (纸本)9781509003662

Technology is quickly revolutionizing our everyday lives, helping us to perform complex tasks. The Internet of Things (IoT) paradigm is getting more and more popular and is key to the development of Smart Cities. Among all the applications of IoT in the context of Smart Cities, realtime parking lot occupancy detection recently gained a lot of attention. Solutions based on computer vision yield good performance in terms of accuracy and are deployable on top of visual sensor networks. Since the problem of detecting vacant parking lots is usually distributed over multiple cameras, adhoc algorithms for content acquisition and transmission are to be devised. A traditional paradigm consists in acquiring and encoding images or videos and transmitting them to a central controller, which is responsible for analyzing such content. A novel paradigm, which moves part of the analysis to sensing devices, is quickly becoming popular. We propose a system for distributed parking lot occupancy detection based on the latter paradigm, showing that onboard analysis and transmission of simple features yield better performance with respect to the traditional paradigm in terms of the overall rate-energyaccuracy performance.

关键词： Parking Lot Occupancy Detection Smart Parking IoT visual sensor network visual Features

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Improving response time in time critical visual sensor network applications

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AD HOC networkS 2014年第Dec.期23卷 65-79页

作者： Felemban, Emad Sheikh, Adil A. Manzoor, Muhammad Asif Umm Al Qura Univ SimplicityLabs Mecca Saudi Arabia Umm Al Qura Univ Sci & Technol Unit Mecca Saudi Arabia Umm Al Qura Univ Dept Comp Engn Mecca Saudi Arabia

Wireless sensor network (WSN) consisting of nodes equipped with cameras or advanced low-cost image sensors is known as a visual sensor network (VSN). The main function of VSN is to capture images and send them to sink nodes for processing. Common applications of a VSN are surveillance, tracking, crowd management, scientific research, etc. Such applications require large amounts of data to be exchanged between camera nodes and sink. Image data is considerably larger than common sensor data such as temperature, humidity, and pressure. For data delivery in VSNs, the communication is constrained by many stringent QoS requirements like delay, jitter and data reliability. Moreover, due to the inherent constraints of WSN such as limited energy, low CPU power, and insufficient memory;the architect of VSN must choose appropriate topology, image compression algorithms, and communication protocols depending on application. In literature, different techniques have been proposed to resolve the bandwidth requirements for the VSN. The majority of these techniques are based on the compression of visual data. This paper focuses on one of these aspects, namely the communication protocol for VSN. In this paper, we present Priority Routing Framework for Image Transmission (PRoFIT), a new routing framework for VSN to deliver critical imagery information with system's time constraint. We demonstrate that PRoFIT improves response time in various VSN applications as compared to priority-less routing techniques. We have implemented PRoFIT along with an image processing application using Contiki and simulated it on Cooja simulator to support our claim. (C) 2014 Elsevier B.V. All rights reserved.

关键词： visual sensor network Priority based routing Contiki operating system Real-time VSN applications Bit-plane encoding Progressive image transmission

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Human Mobility Monitoring in Very Low Resolution visual sensor network

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sensorS 2014年第11期14卷 20800-20824页

作者： Bo, Nyan Bo Deboeverie, Francis Eldib, Mohamed Guan, Junzhi Xie, Xingzhe Nirio, Jorge Van Haerenborgh, Dirk Slembrouck, Maarten Van de Velde, Samuel Steendam, Heidi Veelaert, Peter Kleihorst, Richard Aghajan, Hamid Philips, Wilfried Gent Univ IMinds B-9000 Ghent Belgium Ambient Intelligence Res Lab Stanford CA 94305 USA

This paper proposes an automated system for monitoring mobility patterns using a network of very low resolution visual sensors (30 x 30 pixels). The use of very low resolution sensors reduces privacy concern, cost, computation requirement and power consumption. The core of our proposed system is a robust people tracker that uses low resolution videos provided by the visual sensor network. The distributed processing architecture of our tracking system allows all image processing tasks to be done on the digital signal controller in each visual sensor. In this paper, we experimentally show that reliable tracking of people is possible using very low resolution imagery. We also compare the performance of our tracker against a state-of-the-art tracking method and show that our method outperforms. Moreover, the mobility statistics of tracks such as total distance traveled and average speed derived from trajectories are compared with those derived from ground truth given by Ultra-Wide Band sensors. The results of this comparison show that the trajectories from our system are accurate enough to obtain useful mobility statistics.

关键词： visual sensor network low resolution imagery distributed processing tracking mobility analysis

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Topological Mapping and Navigation Based on visual sensor network

Topological Mapping and Navigation Based on Visual Sensor Ne...

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11th IEEE International Conference on Mechatronics and Automation (ICMA)

作者： Yuan, Wenbo Cao, Zhiqiang Tan, Min Liu, Jingyu Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing Peoples R China

ISBN: (纸本)9781479939794

In this paper, a novel topological mapping approach applied to the navigation mission is proposed based on visual sensor network. Firstly, the natural objects in the scene monitored by visual sensor network are recognized through the inference model based on structural features. Then, topological nodes are designed according to the recognized objects and their spatial structure information, and topological mapping will be fulfilled. On this basis, global localization for mobile robot in camera view can be implemented with HOG feature based detection and tracking. Finally, the robot can make motion decisions for navigation. Our approach does not rely on artificial landmarks and is tested in large-scale office scene. The effectiveness of the proposed approach is verified.

关键词： visual sensor network Topological mapping Navigation Mobile robot

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Multi-view Image Compression for visual sensor network based on Block Compressive Sensing and Multi-phase Joint Decoding

Multi-view Image Compression for Visual Sensor Network based...

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International Conference on Computational Science And Technology (ICCST)

作者： Ebrahim, Mansoor Chong, Chai Wai Sunway Univ Fac Sci & Technol 5 Jalan UnivBandar Sunway Petaling Jaya 46150 Selangor Malaysia

ISBN: (纸本)9781479932412

In this paper, a multi-view image compression framework for the visual sensor network (VSN) is proposed that involve the use of Block-based Compressive Sensing (BCS) and multi-phase joint decoding. In the proposed framework, one of the sensor nodes (encoder) is configured to serve as the reference node, whereas the others as non-reference nodes. The images captured by the reference and non-reference nodes are referred as I-R and I-NR respectively. They are encoded independently using the BCS to produce two measurements that will be transmitted to the host workstation (decoder). In this case, I-NR is always encoded at a lower bitrate when compared to I-R, because the idea is to improve the reconstruction of I-NR with the help of I-R. After the host workstation receives the two measurements, independent decoding is performed first, and then image registration is applied to project I-R onto the same plane of I-NR. The projected I-R is then fused with I-NR using wavelets. Subsequently, the difference between the measurement of the fused image and the measurement of I-NR is calculated. The difference is then decoded and added to I-f to produce the final improved version of I-NR. The simulation results show that the proposed framework is able to improve the quality of I-NR by 1dB to similar to 3dB at lower bitrates, when compared to the conventional BCS.

关键词： Compressive sensing multi-view image visual sensor network joint decoding

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Heterogeneous Feature Fusion-based Optimal Face Image Acquisition in visual sensor network

Heterogeneous Feature Fusion-based Optimal Face Image Acquis...

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IEEE International Instrumentation and Measurement Technology Conference

作者： Kuicheng Lin Xue Wang Sujin Cui Yuqi Tan State Key Laboratory of Precision Measurement Technology and Instrument Department of Precision Instrument Tsinghua University Beijing China

ISBN: (纸本)9781479961153

关键词： optimal face image acquisition fuzzy inference engine visual sensor network face quality assessment

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visual sensor network lifetime maximization by prioritized scheduling of nodes

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JOURNAL OF network AND COMPUTER APPLICATIONS 2013年第1期36卷 409-419页

作者： Hooshmand, M. Soroushmehr, S. M. R. Khadivi, P. Samavi, S. Shirani, S. Isfahan Univ Technol Dept Elect & Comp Engn Esfahan Iran McMaster Univ Dept Elect & Comp Engn Hamilton ON Canada

visual surveillance of a designated air space can be achieved by a randomly distributed camera sensor network spread over a large area. The location and field of view of each battery operated sensor, after a calibration phase, will be known to a central processing node. To increase the lifetime of the network, the density of distributed sensors could be such that a subset of sensors can cover the required air space. As a sensor dies another sensor should be selected to compensate for the dead one and reestablish the complete coverage. This process should be continued until complete coverage is not achievable by the existing sensors. Thereafter, a graceful degradation of the coverage is desirable. The goal is to elongate the lifetime of the network while maintaining a maximum possible coverage of the designated air space. Since the selection of a subset of sensors for complete coverage of the target area is an NP-complete problem, we present a number of heuristics for this case. The proposed methods are categorized in two groups. In one category, the sensors are prioritized based on their visual and communicative properties and the selection is performed according to the prioritizing function. In the other group, we propose traditional evolutionary and swarm intelligence algorithms. The performance of the proposed methods is evaluated through extensive simulations. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： visual sensor network Directional sensors visual coverage Priority based algorithms Genetic algorithm PSO algorithm

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Energy Efficient Routing Mechanism Based on Similarity Guided Graph Neural network and Decision Tree with Golden Eagle Optimization in VSN

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PEER-TO-PEER networkING AND APPLICATIONS 2024年第5期17卷 3408-3423页

作者： Rajkumar, K. Paramasivan, B. Natl Engn Coll Dept CSE Kovilpatti 628503 Tamil Nadu India Natl Engn Coll Dept Informat Technol Kovilpatti 628503 Tamilnadu India

Recent developments in low power sensors have prompted the creation of visual sensor network (VSN). Coverage, availability, network life duration, and energy usage are important issues that arise in VSN. However several energy-efficient protocols have been developed, but those protocols have transmission collisions and energy loss due to increased data redundancy. In order to overcome these challenges, an Energy Efficient Routing based Sleep Scheduling Mechanism (EERSSM) is developed. Camera nodes are randomly deployed in the visual sensor network, and the data is received from the network through a relay node. Energy, distance, and node stability are taken into account while identifying the relay node. The next step is to use a Similarity Graph guided Neural network (SGGNN) to determine whether neighboring nodes detect similar data. If similar information is detected, a similarity measure is computed. When the value of the similarity measure exceeds the threshold, the node goes into the sleep stage while the other nodes are in the wakeup stage. A decision tree is used to calculate the sleep cycle depending on a few factors. The decision tree has a number of hyperparameters, and those parameters are tuned using Golden Eagle Optimization (GEO). When the update cycle is over, the node awakens and joins in the transmission procedure. This proposed energy efficient routing algorithm is tested with several metrics that attain better performance, like 14.42 J average residual energy, 93% packet delivery ratio, 9.3% throughput value, and 770 s network lifetime. Thus, the techniques used in the proposed approach are the better choice for solving the availability, energy consumption, and network lifetime issues in VSN.

关键词： visual sensor network Node stability Sleep wakeup approach Similarity graph guided neural network Golden eagle optimization Decision tree

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