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Decentralized and resource-efficient self-calibration of visual sensor networks

AD HOC networks 2019年 88卷 112-128页

作者： Simonjan, Jennifer Rinner, Bernhard Alpen Adria Univ Klagenfurt Inst Networked & Embedded Syst Klagenfurt Austria

Many multi-camera applications rely on the knowledge of the spatial relationship among the individual nodes. However, establishing such a network-wide calibration is typically a time-consuming task and requires user interaction. In this paper we present a decentralized and resource-aware algorithm for estimating the poses of all network nodes without any user interaction. This self-calibration of the network is achieved in two steps: First, overlapping camera pairs estimate relative positions and orientations by exchanging locally measured distances and angles to detected objects. Second, calibration information of overlapping cameras is spread throughout the network such that poses of non-overlapping cameras can also be estimated. Our approach does not rely on a priori topological information and delivers the extrinsic camera parameters with respect to a common coordinate system. In a simulation study we analyze the performance of our approach concerning the achieved spatial accuracy and computational effort considering noisy measurements and different communication schemes. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Smart cameras visual sensor networks Self-calibration Topology estimation Distributed systems Communication efficiency Resource-awareness

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Data Fusion-Based Multi-Object Tracking for Unconstrained visual sensor networks

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IEEE ACCESS 2018年 6卷 13716-13728页

作者： Jiang, Xiaoyan Fang, Zhijun Xiong, Neal N. Gao, Yongbin Huang, Bo Zhang, Juan Yu, Lei Harrington, Patrick Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai 201620 Peoples R China Northeastern State Univ Dept Math & Comp Sci Tahlequah OK 74464 USA

Camera node perception capability is one of the crucial issues for visual sensor networks, which belongs to the field of Internet of Things. Multi-object tracking is an important feature in analyzing object trajectories across multiple cameras, thus allowing synthesis of data and security analysis of images in various scenarios. Despite intensive research in the last decades, it remains challenging for tracking systems to perform in real-world situations. We therefore focus on key issues of multi-object state estimation for unconstrained multi-camera systems, e.g., data fusion of multiple sensors and data association. Unlike previous work that rely on camera network topology inference, we construct a graph from 2-D observations of all camera pairs without any assumption of network configuration. We apply the shortest path algorithm to the graph to find fused 3-D observation groups. Our approach is thus able to reject false positive reconstructions automatically, and also minimize computational complexity to guarantee feasible data fusion. Particle filters are applied as the 3-D tracker to form tracklets that integrate local features. These tracklets are modeled by a graph and linked into full tracks incorporating global spatial-temporal features. Experiments on the real-world PETS2009 S2/L1 sequence show the accuracy of our approach. Analyses of the different components of our approach provide meaningful insights for object tracking using multiple cameras. Evidence is provided for selecting the best view for a visual sensor network.

关键词： Data fusion graph theory Internet of Things particle filters visual sensor networks

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E-TPE: Efficient Thumbnail-Preserving Encryption for Privacy Protection in visual sensor networks

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ACM TRANSACTIONS ON sensor networks 2024年第4期20卷 1-26页

作者： Zhao, Ruoyu Zhang, Yushu Wen, Wenying Lan, Rushi Xiang, Yong Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Jiangjun Rd Nanjing 211106 Jiangsu Peoples R China Chinese Acad Sci Inst Informat Engn State Key Lab Informat Secur Shucun Rd Beijing 100085 Peoples R China Jiangxi Univ Finance & Econ Sch Informat Management Yuping Ave Nanchang 330032 Jiangxi Peoples R China Guilin Univ Elect Technol Guangxi Key Lab Image & Graph Intelligent Proc Guilin 541004 Guangxi Peoples R China Deakin Univ Sch Informat Technol Burwood Hwy Burwood Vic 3125 Australia

When visual sensor networks (VSNs) enter daily life in society, they not only bring great convenience but also cause people to worry about privacy. Traditional image encryption uses the snowflake effect to protect the privacy, but this can compromise the usability of directly browsing images captured by nodes in VSNs. Recently, thumbnail-preserving encryption (TPE) has been proposed to balance image usability and privacy. However, the Markov chain’s limited connectivity and high time cost, which result in low efficiency, may preclude its application in VSNs. Motivated by this, we propose a novel TPE scheme to protect the image collected in VSNs’ privacy efficiently. We first deeply study the bijective relationship between the three-pixel group and its rank, and then propose a new number method for both, based on which we design the efficient rank mapping. Subsequently, an efficient thumbnail-preserving image encryption via three-pixel rank mapping (E-TPE) is designed, achieving NR security and enhancing the Markov chain’s connectivity. The experiments demonstrate the scheme’s efficiency; that is, it is currently the quickest ideal-TPE scheme with NR security, and a good balance is achieved between usability and privacy.

关键词： Privacy protection usability security visual sensor networks

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Maximal Weighted Coverage Deployment of UAV-Enabled Rechargeable visual sensor networks

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2023年第10期24卷 11293-11307页

作者： Zhu, Xiaojian Zhou, MengChu Changshu Inst Technol Sch Comp Sci & Engn Changshu 215500 Peoples R China Zhejiang Gongshang Univ Sch Informat & Elect Engn Hangzhou 310018 Peoples R China New Jersey Inst Technol Helen & John C Hartmann Dept Elect & Comp Engn Newark NJ 07102 USA

Due to the generation and transmission of video data, the high energy consumption rates of wireless nodes result in short lifetime of a visual sensor network, which has been commonly deployed in 3D space. In many applications, lots of targets need to be covered, but the budgets of both deployment and maintenance are limited. Therefore, how to maximize total weighted target coverage while prolonging network lifetime is of great significance. This work investigates the maximum weighted target coverage deployment of a rechargeable visual sensor network charged by an unmanned aerial vehicle (UAV) in 3D space, which should ensure network permanence and satisfy the budgets of both deployment and maintenance. In this problem, since UAV has a limited energy capacity, it is allowed to return to the depot for energy replenishment more than once in each charging period of wireless nodes so as to increase target coverage. After formulating this problem as a mixed integer nonlinear program, this work proposes a greedy heuristic and a particle swarm optimizer to approximately solve this NP-hard problem. Extensive simulation results reveal that the latter can deliver a better solution despite consuming more time than the former.

关键词： visual sensor networks 3D coverage UAV scheduling node deployment wireless charging

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A learning automata-based algorithm to solve imbalanced k-coverage in visual sensor networks

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2020年第3期39卷 2817-2829页

作者： Bakht, Ahmad Javan Motameni, Homayun Mohamadi, Hosein Islamic Azad Univ Dept Comp Engn Sari Branch Sari Iran Islamic Azad Univ Dept Comp Engn Azadshahr Branch Azadshahr Iran

One of the most important problems in directional sensor networks is k-coverage in which the orientation of a minimum number of directional sensors is determined in such a way that each target can be monitored at least k times. This problem has been already considered in two different environments: over provisioned where the number of sensors is enough to cover all targets, and under provisioned where there are not enough sensors to do the coverage task (known as imbalanced k-coverage problem). Due to the significance of solving the imbalanced k-coverage problem, this paper proposes a learning automata (LA)-based algorithm capable of selecting a minimum number of sensors in a way to provide k-coverage for all targets in a balanced way. To evaluate the efficiency of the proposed algorithm performance, several experiments were conducted and the obtained results were compared to those of two greedy-based algorithms. The results confirmed the efficiency of the proposed algorithm in terms of solving the problem.

关键词： visual sensor networks balanced coverage k-coverage learning automata

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A Distributed Game-Theoretic Approach for Target Coverage in visual sensor networks

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IEEE sensorS JOURNAL 2017年第22期17卷 7542-7552页

作者： Shahrokhzadeh, Behrooz Dehghan, Mehdi Islamic Azad Univ Qazvin Branch Fac Comp & Informat Technol Engn Qazvin 341851416 Iran Amirkabir Univ Technol Dept Comp Engn & Informat Technol Tehran 158754413 Iran

visual sensor networks normally consist of a collection of camera sensors deployed randomly yet densely to fully cover a set of targets. Due to high redundancy incurred, it is possible to both preserve energy and enhance coverage quality by first switching off some sensors and then adjusting the orientations of the remaining ones. The problem is that no global knowledge of the environment is available to be used to decide which sensors should be switched off and which ones should adjust their orientations. In this paper, we propose a new distributed game theoretic approach to full target coverage. A potential game is formulated in which a utility function is designed to consider the tradeoff between coverage quality and energy consumption. In order to solve the game, we present a distributed payoff-based learning algorithm where each sensor has only access to its last two actions played and own utility values. Simulation results show that our proposed game-theoretic approach has greater energy efficiency and can extend the network lifetime, as compared with prior approaches.

关键词： visual sensor networks target coverage network lifetime game theory distributed learning algorithm

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Compress-then-Analyze versus Analyze-then-Compress: What Is Best in visual sensor networks?

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2016年第12期15卷 3000-3013页

作者： Redondi, Alessandro Baroffio, Luca Bianchi, Lucio Cesana, Matteo Tagliasacchi, Marco Politecn Milan Dipartimento Elettron Informaz & Bioingn Pzza Leonardo da Vinci 32 I-20133 Milan Italy

visual sensor networks (VSNs) have attracted the interest of researchers worldwide in the last few years, and are expected to play a major role in the evolution of the Internet-of-Things (IoT). When used to perform visual analysis tasks, VSNs may be operated according to two different paradigms. In the traditional compress-then-analyze paradigm, images are acquired, compressed and transmitted for further analysis. Conversely, in the analyze-then-compress paradigm, image features are extracted by visual sensor nodes, encoded and then delivered to a remote destination where analysis is performed. The question this paper aims to answer is What is the best visual analysis paradigm in VSNs? To do this, first we empirically characterize the rate-energy-accuracy performance of the two aforementioned paradigms. Then, we leverage such models to formulate a resource allocation problem for VSNs. The problem optimally allocates the specific paradigm used by each camera node in the network and the related transmission source rate, with the objective of optimizing the accuracy of the visual analysis task and the VSN coverage. Experimental results over several VSNs instances demonstrate that there is no "winning" paradigm, but the best performance are obtained by allowing the coexistence of the two and by properly optimizing their utilization.

关键词： visual sensor networks local visual features resource allocation SIFT BRISK

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Sparsity-driven bandwidth-efficient decentralized tracking in visual sensor networks

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COMPUTER VISION AND IMAGE UNDERSTANDING 2015年 139卷 40-58页

作者： Cosar, Serhan Cetin, Mujdat Sabanci Univ Fac Engn & Nat Sci TR-34956 Tuzla Istanbul Turkey

Recent developments in low-cost CMOS cameras have created the opportunity of bringing imaging capabilities to sensor networks and a new field called visual sensor networks (VSNs) has emerged. VSNs consist of image sensors, embedded processors, and wireless transceivers which are powered by batteries. Since energy and bandwidth resources are limited, setting up a tracking system in VSNs is a challenging problem. In this paper, we present a framework for human tracking in VSN environments. The traditional approach of sending compressed images to a central node has certain disadvantages such as decreasing the performance of further processing (i.e., tracking) because of low quality images. Instead, in our decentralized tracking framework, each camera node performs feature extraction and obtains likelihood functions. We propose a sparsity-driven method that can obtain bandwidth-efficient representation of likelihoods extracted by the camera nodes. Our approach involves the design of special overcomplete dictionaries that match the structure of the likelihoods and the transmission of likelihood information in the network through sparse representation in such dictionaries. We have applied our method for indoor and outdoor people tracking scenarios and have shown that it can provide major savings in communication bandwidth without significant degradation in tracking performance. We have compared the tracking results and communication loads with a block-based likelihood compression scheme, a decentralized tracking method and a distributed tracking method. Experimental results show that our sparse representation framework is an effective approach that can be used together with any probabilistic tracker in VSNs. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Camera networks visual sensor networks Human tracking Sparse representation Designing overcomplete dictionaries

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Exploiting the sensing relevancies of source nodes for optimizations in visual sensor networks

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MULTIMEDIA TOOLS AND APPLICATIONS 2013年第3期64卷 549-579页

作者： Costa, Daniel G. Guedes, Luiz Affonso Univ Fed Rio Grande do Norte Dept Comp & Automat BR-59072970 Natal RN Brazil State Univ Feira de Santana Dept Technol BR-44036900 Feira De Santana BA Brazil

Wireless ad-hoc networks composed of resource-constrained camera-enabled sensors can provide visual information for a series of monitoring applications, enriching the understanding of the physical world. In many cases, source nodes may have different sensing relevancies for the monitoring functions of the applications, according to the importance of the visual information retrieved from the monitored field. As a direct result, high quality is only required for the most relevant information and, as it is expected that many visual monitoring applications can tolerate some quality loss in the data received from the least relevant source nodes, the network operation can be optimized exploiting this innovative concept. As a novel global QoS parameter, we envisage that the sensing relevancies of source nodes can be considered for a series of optimizations in different aspects of the wireless sensor network operation, achieving energy saving or assuring high quality transmission for the most relevant data. In this paper we discuss some approaches for the establishment of the sensing relevancies of the nodes and propose a protocol to support them. Moreover, we present two practical examples of optimizations based on the sensing relevancies of source nodes that transmit still images of the monitored field, addressing issues as energy-efficient data transmission and packet prioritization in intermediate nodes.

关键词： visual sensor networks Sensing relevance Network optimization Energy-efficiency Packet prioritization

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Lifetime improvement of visual sensor networks for target coverage through uniform energy consumption

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INTERNATIONAL JOURNAL OF AD HOC AND UBIQUITOUS COMPUTING 2013年第4期14卷 249-266页

作者： Hosseini, Mojtaba Dehghan, Mehdi Pedram, Hossein Amirkabir Univ Technol Comp Engn & Informat Technol Dept Tehran Iran

In this paper, a novel method is proposed for inducing uniformity in energy consumption across the entire network area. This method prolongs the durability of the target coverage task. Moreover, it is shown that the optimised selection of the sensors in each timeslot does not lead to an optimum selection across the lifetime of the network due to non-uniformity in energy consumption pattern. Uniformity control is achieved using the sensors' panning capability to select the sensing area. The major notion of energy uniformity in this paper is typified with the network area sections level. For this criterion, sensor selection has been modeled as a binary integer programming (BIP) problem, and optimal solutions have been obtained for both point target model and circular target model which are used in k-coverage and full-angle coverage, respectively. Furthermore, a distributed algorithm has also been proposed. Experimental results demonstrate that exerting uniformity control can significantly increase the lifetime of the network.

关键词： VSNs visual sensor networks directional sensor sensor selection sensor reconfiguration binary integer programming lifetime maximisation energy consumption uniformity k-coverage full angle coverage

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