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检索条件"主题词=Visual Sensor Networks"

共 124 条记录，以下是41-50 订阅

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A DISTRIBUTED SOLUTION TO DETECT TARGETS IN CROWDS USING visual sensor networks

A DISTRIBUTED SOLUTION TO DETECT TARGETS IN CROWDS USING VIS...

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2nd ACM/IEEE International Conference on Distributed Smart Cameras

作者： Qian, Cheng Qi, Hairong Viatronix Inc Stony Brook NY 11790 USA Univ Tennessee EECS Dept Knoxville TN 37996 USA

ISBN: (纸本)9781424426645

visual sensor networks (VSNs) have been attracting more and more research attention nowadays. This paper presents our design of a distributed solution for a VSN to detect targets in a large and crowded field. Due to ambiguities in local visual information and ubiquitous visual occlusions, obtaining accurate detection results requires fully utilizing the entire visual information acquired across the network. In our solution, a Back-Projecting-Flooding (BPF) method is proposed to integrate related visual information, which is followed by a Distributed-Highest-Confidence-First (DHCF) method that implements an iterative global target selection process in a distributed manner. Compared with its centralized version, this solution not only achieves equivalent detection accuracy but also reduces and balances the amount of energy consumption across the network. Simulation results are presented to show the effectiveness of this solution.

关键词： visual sensor networks target detection visual occlusions

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PhD Forum: Coverage Redundancy in visual sensor networks 12

PhD Forum: Coverage Redundancy in Visual Sensor Networks

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12th International Conference on Distributed Smart Cameras (ICDSC)

作者： Vejdanparast, Arezoo Aston Univ ALICE Birmingham W Midlands England

ISBN: (纸本)9781450365116

When a network of cameras with adjustable zoom lenses is tasked with object coverage, an important question is how to determine the optimal zoom level for each camera. While covering a smaller area allows for higher detection likelihood, overlapping fields of view introduce a redundancy which is vital to fault tolerance and acquisition of multiple perspectives of targets. In our research, we study the coverage redundancy problem in visual sensor networks formalised as the k-coverage (e.g. [1, 3, 4]), where k represents the number of cameras covering a specific point. However, we are not trying to cover static points in the environment but rather mobile points that may change their position over time. A visual sensor network (VSN) that we study, is composed of omni-directional cameras C = {c1, c2, . . ., ci, . . ., c_n} with 360-degree views, each equipped with an adjustable zoom lens. The circular field of view (FOV) of camera c_i has a range r_i that corresponds to current zoom level. The network is tasked to cover a set of moving objects O = {o1, o2, . . ., o_j, . . ., o_m}. We consider a point to be covered by a camera if it lies within the camera's FOV and is detectable by that camera. In order to address detectability, inspired by the work by Esterle et al. [2], we propose a resolution-based confidence model for our cameras. For a camera with a given resolution, the model identifies the classification success rate based on pixel density across all available objects within that cameras FOV. If the rate is above a certain threshold τ then the object is marked as covered. This enables each individual camera to identify the number of objects it covers at runtime. Before we describe details of our confidence model, we indicate a few important factors that affects the accuracy of the model;i) current zoom level has an inherent impact on the quality of the coverage. It invokes a trade-off between the size of area cover

关键词： visual sensor networks smart cameras online learning machine learning approaches decentralised systems

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Distributed Object Recognition in visual sensor networks

Distributed Object Recognition in Visual Sensor Networks

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IEEE International Conference on Communications (ICC)

作者： Paris, Stefano Redondi, Alessandro Cesana, Matteo Tagliasacchi, Marco Univ Paris 05 Math & Algorithm Sci Lab France Res Ctr Huawei Technol Co LtdLIPADE Paris France Politecn Milan Dipartimento Elettron Informaz & Bioingn I-20133 Milan Italy

ISBN: (纸本)9781467364324

This work focuses on visual sensor networks (VSNs) which perform visual analysis tasks such as object recognition. There, the goal is to find the image in a reference database which is the closest match to the image captured by camera sensor nodes. Recognition is performed by relying on visual features extracted from the acquired image, which are matched against a database of labeled features in order to find the closest image match. The matching functionalities are often implemented at a central controller outside the VSN. In contrast, we study the performance trade-offs involved in distributing the matching functionalities inside the VSN by letting sensor nodes performing parts of the matching process. We propose an optimization framework to optimally distribute the matching task to in-network sensor nodes with the goal of minimizing the overall completion time of the recognition task. The proposed optimization framework is then used to assess the performance of distributed matching, comparing it to a traditional, centralized approach in realistic VSN scenarios.

关键词： Cache Placement Object Recognition visual sensor networks

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Nodes Placement for Optimizing Coverage of visual sensor networks

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10th Pacific Rim Conference on Multimedia

作者： Wang, Chang Qi, Fei Shi, Guang-Ming Xidian Univ Key Lab Intelligent Percept & Image Understanding Minist Educ China Xian 710071 Shaanxi Peoples R China

ISBN: (纸本)9783642104664

visual sensor networks have become a research focus with its expanding application domains How to achieve optimal coverage to improve visual network's capability of obtaining regional information is a critical issue As a visual sensor has a bounded field of view, a random deployment of network sensors can hardly solve this issue This paper proposes a bounded observation field sensing model based on the sensing feature of visual sensor According to this model, a sensor placement method is devised by means of multi-agent genetic algorithm (MAGA) The positions and poses of sensors which can enhance the coverage can be effectively worked out by this placement algorithm. thus the visual network's capability of obtaining regional in can be improved Experiment results show that the algorithm proposed is effective in both 2D and 3D scenes

关键词： visual sensor networks bounded observation field sensing model optimal coverage sensor placement

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An Optimised Indoor Deployment of visual sensor networks 16

An Optimised Indoor Deployment of Visual Sensor Networks

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16th International Conference on Signal-Image Technology and Internet-Based Systems (SITIS)

作者： Faga, Yves Abdou, Wahabou Dubois, Julien Univ Bourgogne Franche Comte ImViA Lab Dijon France Univ Bourgogne Franche Comte LIB Lab Dijon France

ISBN: (纸本)9781665464956

This paper deals with the problem of deploying a sensor network to monitor an area. More specifically, we consider sensor nodes that are equipped with smart cameras. We refer to this network as visual sensor network (VSN). The cameras used in this study are directional and must be placed along the walls to ensure better coverage in an indoor environment. The optimisation problem has two objective functions: (i) maximise the overall coverage of the study area and (ii) maximise the coverage of some spots called areas of interest. To deal with this problem, we propose an approach based on a genetic algorithm and a simulation tool to measure the cameras' fields of view (based on ray tracing). The results obtained show that the algorithm adapts well to the presence of obstacles and/or areas of interest. Moreover, the algorithm succeeds in simultaneously optimising the two objective functions without being trapped by local optima.

关键词： sensor deployment visual sensor networks multi-objective optimisation

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MULTI-VIEW DISTRIBUTED SOURCE CODING OF BINARY FEATURES FOR visual sensor networks 41

MULTI-VIEW DISTRIBUTED SOURCE CODING OF BINARY FEATURES FOR ...

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41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Monteiro, Nuno Brites, Catarina Pereira, Fernando Ascenso, Joao Inst Super Tecn Inst Telecomunicacoes Lisbon Portugal

ISBN: (纸本)9781479999880

visual analysis algorithms have been mostly developed for a centralized scenario where all visual data is acquired and processed at a central location. However, in visual sensor networks (VSN), several constraints in computational power, energy and bandwidth require a radically different approach, notably a paradigm shift from centralized to distributed visual processing. In the new paradigm, visual data is acquired and features are extracted at the sensing nodes locations to be after transmitted to enable further analysis at some central location. In such scenario, one of the key challenges is to design suitable feature coding schemes that are able to exploit the correlation among the features corresponding to (partially) overlapped views of the same visual scene. To achieve efficient coding, it is proposed to employ the distributed source coding paradigm as it does not require any communication between the sensing nodes (rather expensive in VSN) and it is parsimonious in terms of computational resources. Experimental results show that significant accuracy and compression gains (up to 37.36%) can be achieved when coding features extracted from multiple views.

关键词： distributed source coding feature coding multi-view coding visual sensor networks

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PTZ Camera Scheduling for Selected Area Coverage in visual sensor networks 35

PTZ Camera Scheduling for Selected Area Coverage in Visual S...

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2015 IEEE 35th International Conference on Distributed Computing Systems

作者： Guo, Ling Zhu, Yuqing Li, Deying Kim, Donghyun Renmin Univ China Sch Informat Beijing Peoples R China Calif State Univ Los Angeles Dept Comp Sci Los Angeles CA 90032 USA N Carolina Cent Univ Dept Math & Phys Durham NC USA

ISBN: (纸本)9781467372145

visual sensor networks (VSNs) can track multiple pedestrians and capture high-quality videos of the monitored area. Therefore, VSNs is ideal for providing good broadcast service. In sports broadcasting, a basic requirement for broadcasters is to report the significant events as quickly as possible when they take place. To meet this requirement, we propose the Camera Scheduling for selected area coverage problem (CamS). Considering that Pan-Tilt-Zoom (PTZ) camera sensor has the flexibility of configuring its angle of view in both horizontal and vertical dimensions, we apply PTZ camera sensors to solve CamS. A polynomial time optimal algorithm that schedules PTZ camera sensors elegantly is devised for CamS. We set many realistic application scenarios in simulation and thoroughly study how our algorithm's performance is affected by different environmental parameters, including angle velocity, the number of camera sensors and the number of sub-areas.

关键词： visual sensor networks PTZ camera Maximum Weight Perfect Matching Selected Area Coverage

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Multifocus image fusion based on compressive sensing for visual sensor networks 22

Multifocus image fusion based on compressive sensing for vis...

引用

22nd Iranian Conference on Electrical Engineering (ICEE)

作者： Kazemi, Vahdat Seyedarabi, Hadi Aghagolzadeh, Ali Univ Tabriz Fac Elect & Comp Engn Tabriz Iran Babol Univ Technol Fac Elect & Comp Engn Babol Sar Iran

ISBN: (纸本)9781479944095

In this paper, we present a new and efficient multifocus image fusion based on compressive sensing in visual sensor networks. The energy consumption and bandwidth are mean factor in visual sensor networks which determine the lifetime of sensors. Thus, for reducing the energy consumption and bandwidth in transmission;the proposed method uses compressive sensing for fusion of multifocus images. The experimental results show that the proposed approach can achieve a higher fusion quality than some exiting fusion schemes.

关键词： multifocus image fusion compressive sensing visual sensor networks discrete wavelet transform

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QUALITY-DRIVEN POWER CONTROL AND RESOURCE ALLOCATION IN WIRELESS MULTI-RATE visual sensor networks

QUALITY-DRIVEN POWER CONTROL AND RESOURCE ALLOCATION IN WIRE...

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19th IEEE International Conference on Image Processing (ICIP)

作者： Katsenou, Angeliki V. Kondi, Lisimachos P. Parsopoulos, Konstantinos E. Bentley, Elizabeth S. Univ Ioannina Dept Comp Sci GR-45110 Ioannina Greece Air Force Res Lab Rome NY 13441 USA

ISBN: (纸本)9781467325332;9781467325349

In the present paper, we deal with the problem of allocating the network resources in multi-rate Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor networks (VSNs). We consider a single-cell system where each node uses the same chip rate, but can transmit at a different bit rate. In wireless VSNs, we face the constraints of limited power lifetime and of an error-prone environment, mainly due to attenuation and interference. The proposed cross-layer scheme enables the Centralized Control Unit (CCU) to jointly allocate the transmission power, the transmission bit rate and the source-channel coding rates for each VSN node in order to optimize the delivered video quality. The transmission power of each visual sensor assumes values from a continuous range, while the rest of the resources take values chosen from an available discrete set. The numerical results demonstrate the performance of the proposed multi-rate scheme vs a single-rate system.

关键词： Multi-rate DS-CDMA Power Control Resource Allocation visual sensor networks

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Online Zoom Selection Approaches for Coverage Redundancy in visual sensor networks 18

Online Zoom Selection Approaches for Coverage Redundancy in ...

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12th International Conference on Distributed Smart Cameras (ICDSC)

作者： Vejdanparast, Arezoo Lewis, Peter R. Esterle, Lukas Aston Univ ALICE Birmingham W Midlands England

ISBN: (纸本)9781450365116

When a network of cameras with adjustable zoom lenses is tasked with object coverage, an important question is how to determine the optimal zoom level for each camera. While covering a smaller area allows for higher detection likelihood, overlapping fields of view introduce a redundancy which is vital to fault tolerance and acquisition of multiple perspectives of targets. In this paper, we study the coverage redundancy problem in visual sensor networks formalised as the k-coverage. We propose a resolution-based detection model that enables the exploration of the zoom level impact on the extension of coverage redundancy. Given mobile targets, we investigate the network-wide best k-coverage using global knowledge of the network. We explore the advantages and disadvantages of this approach and propose a realistic zoom adaptation model for cameras under a new zoom level proximity constraint. Further to the global approach, which aim to provide the highest possible k-coverage across the network, we study the performance of several online heuristics and learning approaches which use only local knowledge to approximate the highest k-coverage under our zoom level proximity constraint. Furthermore, we show that in many scenarios the dynamic behaviour resulting from the online learning approaches is not only computationally less expensive but also leads to a significant improvement on the level of coverage redundancy compared with heuristic approaches. This becomes even more apparent when objects follow scripted movement patterns.

关键词： visual sensor networks smart cameras online learning machine learning approaches decentralised systems

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