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3rd ACM/IEEE International Conference on Distributed Smart Cameras

作者： Sulic, Vildana Pers, Janez Kristan, Matej Kovacic, Stanislav Univ Ljubljana Fac Elect Engn Machine Vis Lab SI-1000 Ljubljana Slovenia

ISBN: (纸本)9781424446193

We propose a framework for hierarchical feature distribution scheme for object recognition in a network of visual sensors. The key of our approach is the principle that individual nodes in the network hold only a small amount of information about objects seen by the network, however, this small amount is sufficient to efficiently route queries through the network. Preliminary results suggest that amount of data transmitted through the network can be reduced in comparison to simpler feature distribution schemes.

关键词： visual sensor network computer vision object recognition

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Coverage Estimation in Floorplan visual sensor networks

Coverage Estimation in Floorplan Visual Sensor Networks

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8th IEEE International Conference on Broadband, Wireless Computing, Communication and Applications (BWCCA)

作者： Attar, Ahmad Movahedian Izadi, M. Hamed Movahedian, Maedeh Yarahmadian, Shantia Isfahan Univ Technol Elect & Comp Engn Dept Esfahan Iran Ecole Polytech Fed Lausanne Dept Elect Engn Lausanne Switzerland Electrotech Unternehmen GmbH Schopfheim Germany Mississippi State Univ Dept Math & Stat Mississippi State MS 39762 USA

ISBN: (纸本)9780769550930

The issue of Coverage in visual sensor networks (VSNs) has attracted considerable attention due to sensors unique directional sensing characteristic. It answers the question that how well the target field is monitored by a network of sensors with video/image capturing capability. In floorplan scenario the network is to monitor a plane parallel to the sensors' deployment plane. Coverage probability estimation based on both the sensors and the network related parameters is a fundamental issue in this field. For a large scale application in which the sensors' deployment is done by dropping sensors from an airplane, random sensors' placement and orientation according to their respective distribution is a practical assumption. Although some studies exist on the coverage problem of floorplan VSNs, none of them has derived a closed form solution for the coverage estimation, which is the main contribution of this paper. The Simulation results validated the proposed mathematical.

关键词： visual sensor network floorplan coverage

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Feature-based Vehicle Tracking at Roundabouts in visual sensor networks 17

Feature-based Vehicle Tracking at Roundabouts in Visual Sens...

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17th International Multi-Conference on Systems, Signals and Devices (SSD)

作者： Eleuch, Salma Khouja, Nadia Erseghe, Tomaso Tlili, Fethi Univ Padua SupCom Tunis Tunisia SupCom Grescom Lab Tunis Tunisia Univ Padua Padua Italy

ISBN: (纸本)9781728110806

During the last decade, visual monitoring has gained an increasing interest especially in the field of smart cities and intelligent transportation systems. This paper describes a feature-based vehicle tracking system in visual sensor networks at roundabouts. In the proposed system, the tasks for vehicle tracking are divided among smart camera nodes and the receiver. Smart camera nodes are embedded devices equipped with camera sensor, multiprocessors for video processing and computer vision tasks, and an RF transceiver for wireless communication. They are responsible for the vehicle detection and classification as well as features extraction. In order to satisfy the constraints of the visual sensor network in terms of power and communication resources, we assume that only the features are transmitted to the sink node. The received features will then be used to retrieve the vehicle trajectories. In order to train the vehicle classifier used at the camera nodes and to test the proposed tracking approach, a training database was built by placing cameras around a realworld roundabout. The system is shown to be capable of tracking vehicles even in partial occlusion cases.

关键词： Features intelligent transportation systems roundabout vehicle tracking visual sensor network

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Resource Management in visual sensor networks using Nash Bargaining Solution in Generalized Fading

Resource Management in Visual Sensor Networks using Nash Bar...

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10th IEEE Consumer Communications and networking Conference (CCNC)

作者： Odejide, Olusegun O. Bentley, Elizabeth S. Kondi, Lisimachos P. Matyjas, John D. USAF Res Lab Rome NY 13441 USA Univ Ioannina Dept Comp Sci GR-45110 Ioannina Greece

ISBN: (纸本)9781467331333;9781467347358

In this paper we consider the problem of resource management for a Direct Sequence Code Division Multiple Access (DS-CDMA) wireless visual sensor network (VSN) in a generalized fading environment. In a VSN application, the primary goal is ensuring that maximum video quality is achieved in spite of the prevailing network resource constraints. The Nash Bargaining Solution (NBS) was used in determining the transmission power and source and channel coding rates for each node. The nodes in the network negotiate in order to determine their transmission parameters. The task is to optimize the transmission powers (which are continuous) and the source and channel coding rates (which are discrete) for all the network nodes. Particle Swarm Optimization (PSO) is used to solve the mixed-integer optimization that arises. The analysis was carried out for a myriad of wireless multipath fading environments using a unified moment generating function (MGF) approach.

关键词： visual sensor network cross layer optimization Nash bargaining solution game theory multipath fading particle swarm optimization moment generating function

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Resource-aware State Estimation in visual sensor networks with Dynamic Clustering 4

Resource-aware State Estimation in Visual Sensor Networks wi...

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4th International Conference on sensor networks (sensorNETS)

作者： Schranz, Melanie Rinner, Bernhard Alpen Adria Univ Klagenfurt Inst Networked & Embeddod Syst Klagenfurt Austria

ISBN: (纸本)9789897580864

Generally, resource-awareness plays a key role in wireless sensor networks- due the limited capabilities in processing, storage and communication. In this paper we present a resource-aware cooperative state estimation facilitated by a dynamic cluster-based protocol in a visual sensor network (VSN). The VSN consists of smart cameras. which process and analyze the captured data locally. We apply a state estimation algorithm to improve the tracking results of the cameras. To design a lightweight protocol, the final aggregation of the observations and state estimation are only performed by the cluster head. Our protocol is based on a market-based approach in which the cluster head is elected based-on-the available resources and a visibility parameter of the object gained by the cluster members. We show in simulations that our approach reduces the costs for state estimation and communication as compared to a fully distributed approach. As resource-awareness is the focus of the cluster-based protocol we can accept a slight degradation of the accuracy on the object's state estimation by a standard deviation of about 1.48 length units to the available ground truth.

关键词： visual sensor network Resource Distribution Wireless Communication Negotiation Theory Decentralized Processing

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Resource Allocation in visual sensor networks Using a Reinforcement Learning Framework

Resource Allocation in Visual Sensor Networks Using a Reinfo...

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18th International Conference on Digital Signal Processing (DSP)

作者： Pandremmenou, Katerina Tziortziotis, Nikolaos Kondi, Lisimachos P. Blekas, Konstantinos Univ Ioannina Dept Comp Sci GR-45110 Ioannina Greece

ISBN: (纸本)9781467358057

In recent years, video delivery over wireless visual sensor networks (VSNs) has gained increasing attention. The lossy compression and channel errors that occur during wireless multimedia transmissions can degrade the quality of the transmitted video sequences. This paper addresses the problem of cross-layer resource allocation among the nodes of a wireless direct-sequence code division multiple access (DS-CDMA) VSN. The optimal group of pictures (GoP) length during the encoding process is also considered, based on the motion level of each video sequence. Three optimization criteria that optimize a different objective function of the video qualities of the nodes are used. The nodes' transmission parameters, i.e., the source coding rates, channel coding rates and power levels can only take discrete values. In order to tackle the resulting optimization problem, a reinforcement learning (RL) strategy that promises efficient exploration and exploitation of the parameters' space is employed. This makes the proposed methodology usable in large or continuous state spaces as well as in an online mode. Experimental results highlight the efficiency of the proposed method.

关键词： Cross-layer optimization group of pictures length Markov decision processes reinforcement learning resource allocation visual sensor network

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Kalai-Smorodinsky Bargaining Solution for Optimal Resource Allocation over Wireless DS-CDMA visual sensor networks

Kalai-Smorodinsky Bargaining Solution for Optimal Resource A...

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Conference on visual Information Processing and Communication III

作者： Pandremmenou, Katerina Kondi, Lisimachos P. Parsopoulos, Konstantinos E. Univ Ioannina Dept Comp Sci GR-45110 Ioannina Greece

ISBN: (纸本)9780819489524

Surveillance applications usually require high levels of video quality, resulting in high power consumption. The existence of a well-behaved scheme to balance video quality and power consumption is crucial for the system's performance. In the present work, we adopt the game-theoretic approach of Kalai-Smorodinsky Bargaining Solution (KSBS) to deal with the problem of optimal resource allocation in a multi-node wireless visual sensor network (VSN). In our setting, the Direct Sequence Code Division Multiple Access (DS-CDMA) method is used for channel access, while a cross-layer optimization design, which employs a central processing server, accounts for the overall system efficacy through all network layers. The task assigned to the central server is the communication with the nodes and the joint determination of their transmission parameters. The KSBS is applied to non-convex utility spaces, efficiently distributing the source coding rate, channel coding rate and transmission powers among the nodes. In the underlying model, the transmission powers assume continuous values, whereas the source and channel coding rates can take only discrete values. Experimental results are reported and discussed to demonstrate the merits of KSBS over competing policies.

关键词： visual sensor network DS-CDMA cross-layer optimization resource allocation Kalai-Smorodinsky bargaining solution game theory

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Self-calibration in visual sensor networks equipped with RGB-D cameras 40

Self-calibration in visual sensor networks equipped with RGB...

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40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015

作者： Wang, Xiaoqin Sekercioglu, Y. Ahmet Drummond, Tom ARC Centre of Excellence for Robotic Vision Monash University Australia

ISBN: (纸本)9781467369978

We consider the self-calibration problem (estimation of location and orientation of multiple camera sensors), in visual sensor networks equipped with RGB-D cameras. We propose two algorithms based on feature matching and relative pose estimation. First one uses Floyd-Warshall algorithm, and can accurately estimate the camera locations. On the other hand, the second algorithm is more scalable than the first one, and can be used in large networks if high accuracy is not an issue. Numerical results demonstrate that both algorithms, depending on the network topology, can be used for self-calibration in RGB-D equipped visual sensor networks. © 2015 IEEE.

关键词： RGB-D camera Self-calibration visual sensor network

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Coverage Overlaps Reduction with Delaunay Triangulation for visual sensor networks

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JOURNAL OF INTERNET TECHNOLOGY 2019年第3期20卷 809-816页

作者： Zhang, Shun-Miao Huang, De-Gen Dalian Univ Technol Sch Comp Sci & Technol Dalian Peoples R China Fujian Univ Technol Fujian Prov Key Lab Big Data Min & Applicat Fuzhou Fujian Peoples R China Fujian Univ Technol Coll Informat Sci & Engn Fuzhou Fujian Peoples R China

A visual sensor network (VSN) employs visual (camera) sensors instead of scalar sensors to establish the wireless network for wide area monitoring and target tracking. The visual sensing coverage of a VSN is quite related to the sensing direction and sensing angle of each camera sensors in the network. Many research issues of VSNs are similar but much different from the ones of ordinary scalar sensor networks, and the visual coverage issue is more specific. In the past years, a great number of research literatures have been proposed to address the coverage issues for ordinary scalar sensor networks. A part of the existing approaches use geometric structure concepts in the researches. However, utilizing geometric structures to solve visual sensing coverage has not drawn much attention of researches. This study, therefore, utilizes a geometric structure of Delaunay Triangulation with its characteristics to improve overall visual coverage of a sensing field for VSNs. The results of evaluation with simulations show the proposed approach performs very well and obtains a significant visual coverage improvement for VSNs. This could be a reference basis for further studies.

关键词： visual sensor network visual coverage Delaunay triangulation Geometry

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Coverage Estimation for Crowded Targets in visual sensor networks

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ACM TRANSACTIONS ON sensor networkS 2012年第3期8卷 26-26页

作者： Karakaya, Mahmut Qi, Hairong Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN 37996 USA

Coverage estimation is one of the fundamental problems in sensor networks. Coverage estimation in visual sensor networks (VSNs) is more challenging than in conventional 1-D (omnidirectional) scalar sensor networks (SSNs) because of the directional sensing nature of cameras and the existence of visual occlusion in crowded environments. This article represents a first attempt toward a closed-form solution for the visual coverage estimation problem in the presence of occlusions. We investigate a new target detection model, referred to as the certainty-based target detection (as compared to the traditional uncertainty-based target detection) to facilitate the formulation of the visual coverage problem. We then derive the closed-form solution for the estimation of the visual coverage probability based on this new target detection model that takes visual occlusions into account, According to the coverage estimation model, we further propose an estimate of the minimum sensor density that suffices to ensure a visual K-coverage in a crowded sensing field. Simulation is conducted which shows extreme consistency with results from theoretical formulation, especially when the boundary effect is considered. Thus, the closed-form solution for visual coverage estimation is effective when applied to real scenarios, such as efficient sensor deployment and optimal sleep scheduling.

关键词： Algorithms Theory Measurement Performance Directional coverage visual occlusions visual sensor network coverage estimation

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