Distributed topology management for wireless multimedia sensor networks: exploiting connectivity and cooperation

In this paper, we propose a distributed topology management algorithm, named T‐Must, which orchestrates coalition formation game between camera and scalar sensor (SS) nodes, for use in wireless multimedia sensor networks. In the proposed solution, connectivity among the peer camera sensor (CS) nodes is maintained, and coverage is ensured between them. Only the scalar data are not sufficient to describe an event in a particular monitored area. In many cases, multimedia data (specifically, video data) are required to provide more precise information about the event. As the CS nodes, which sense and transmit multimedia data, are costlier than the SS nodes, the former are deployed in the monitored area in lesser numbers compared to the latter ones. In case of CS nodes, power consumption due to sensing is also significant, similar to power consumption for the transmission and reception of packets. Therefore, in this work, in order to increase the network lifetime, topology is controlled by forming coalition between the CS and SS nodes. Upon occurrence of an event, the SS nodes send scalar data to their associated CS nodes. If the scalar data received from SS nodes cross a preconfigured threshold, the associated CS node in the coalition starts sensing the event, captures the video data, and forwards the video data toward other coalitions or sink. Copyright © 2014 John Wiley & Sons, Ltd.     

Adaptive cost efficient deployment strategy for homogeneous wireless camera sensors

Availability of low cost low power camera sensors is likely to make possible applications that may otherwise have been infeasible. In this paper we investigate a cost efficient camera sensor deployment strategy based on random deployment of homogeneous sensors to monitor and/or surveillance a region of interest. We assume that there are costs associated with the sensors as well as with the deployments and our goal is to minimize the total cost while satisfying the desired coverage requirement. We consider two cases which assume the sensing field is obstacle free or with obstacles, and we develop analytical methods to derive the expected coverage of a single sensor as well as the joint coverage for a given number of homogenous camera sensors. Following this we propose an adaptive sensor deployment strategy, which deploys different number of sensors in each iteration, based on our analytical method. We then evaluate the expected cost of our deployment strategy by deriving expressions for the number of deployments and the number of sensors deployed during each deployment as a function of the probability distributions of joint coverage by sensors. We carry out simulation studies to validate the analytical results. Simulation studies are also used to demonstrate that our deployment strategy leads to near optimal values of sensors and deployments and hence achieves the overall low cost.     

Efficient Sensing Topology Management for Spatial Monitoring with Sensor Networks

We focus on exploiting redundancy for sensor networks in the context of spatial interpolation. The network acts as a distributed sampling system, where sensors periodically sample a physical phenomenon of interest, e.g. temperature. Samples are then used to construct a continuous spatial estimate of the phenomenon over time through interpolation. In this regime, the notion of sensing range typically utilized to characterize redundancy in event detection applications is meaningless and sensor selection schemes based on it become unsuitable. Instead, this paper presents pragmatic approaches for exploiting redundancy in such applications. Their underlying characteristic is that no a-priori assumptions need to be made on the statistical properties of the physical phenomenon. These are instead learned by the network after deployment. Our approaches are evaluated through real as well as synthetic sensor network data showing that significant reductions in the number of active sensors are indeed possible.     

Coverage analysis for target localization in camera sensor networks

Camera sensor networks have recently emerged as a critical research topic. In this paper, we investigate the coverage problem for camera sensor networks. Specially, compared to the coverage problem for target detection which has been intensively studied, this paper studies the coverage problem from the perspective of target localization. We first propose a novel localization‐oriented sensing model based on the perspective projection of the camera sensors. Then, under the random uniform deployment strategy, we analyze how the probability of the localization‐oriented coverage (L‐coverage for short) changes with the sensors number and the parameters of the proposed sensing model. Finally, we conduct extensive simulations to validate our model and theoretical analysis about L‐coverage probability. The obtained results show that our scheme can be effectively applied for practical scenarios. Copyright © 2011 John Wiley & Sons, Ltd.     

An Introduction to Distributed Smart Cameras

Distributed smart cameras (DSCs) are real-time distributed embedded systems that perform computer vision using multiple cameras. This new approach has emerged thanks to a confluence of simultaneous advances in four key disciplines: computer vision, image sensors, embedded computing, and sensor networks. Processing images in a network of distributed smart cameras introduces several complications. However, we believe that the problems DSCs solve are much more important than the challenges of designing and building a distributed video system. We argue that distributed smart cameras represent key components for future embedded computer vision systems and that smart cameras will become an enabling technology for many new applications. We summarize smart camera technology and applications, discuss current trends, and identify important research challenges.      

Challenging issues in visual sensor networks [accepted from open call]

Wireless sensor networks are an important research area that has attracted considerable attention. Most of this attention, however, has been concentrated on WSNs that collect scalar data such as temperature and vibration. Scalar data can be insufficient for many applications such as automated surveillance and traffic monitoring. In contrast, camera sensors collect visual data, which are rich in information and hence offer tremendous potential when used in WSNs. However, they raise new challenges such as the transmission of visual data with high computational and bandwidth requirements in mainly low-power visual sensor networks. In this article we highlight the challenges and opportunities of VSNs. We discuss major research issues of VSNs, specifically camera coverage optimization, network architecture, and low-power visual data processing and communication, and identify enabling approaches in this area.     

传感器网络中基于数据融合的栅栏覆盖控制研究

该文采用概率性感知模型,并利用数据融合技术构造虚拟节点来增加节点覆盖区域。在此基础上,提出一种栅栏覆盖控制算法。算法借助分治法构造栅栏,以减少节点间通信开销;并调度传感器使冗余节点睡眠,达到减少能耗和延长网络寿命的目的。分析和实验结果表明,针对所提问题设计的模型和算法可有效增加节点覆盖范围及节点间最大间隔距离,且在栅栏数、网络寿命等性能上均优于基于节点监测数据未融合的栅栏覆盖控制算法。     

Geometry-based distributed scene representation with omnidirectional vision sensors

This paper addresses the problem of efficient representation of scenes captured by distributed omnidirectional vision sensors. We propose a novel geometric model to describe the correlation between different views of a 3-D scene. We first approximate the camera images by sparse expansions over a dictionary of geometric atoms. Since the most important visual features are likely to be equivalently dominant in images from multiple cameras, we model the correlation between corresponding features in different views by local geometric transforms. For the particular case of omnidirectional images, we define the multiview transforms between corresponding features based on shape and epipolar geometry constraints. We apply this geometric framework in the design of a distributed coding scheme with side information, which builds an efficient representation of the scene without communication between cameras. The Wyner-Ziv encoder partitions the dictionary into cosets of dissimilar atoms with respect to shape and position in the image. The joint decoder then determines pairwise correspondences between atoms in the reference image and atoms in the cosets of the Wyner-Ziv image in order to identify the most likely atoms to decode under epipolar geometry constraints. Experiments demonstrate that the proposed method leads to reliable estimation of the geometric transforms between views. In particular, the distributed coding scheme offers similar rate-distortion performance as joint encoding at low bit rate and outperforms methods based on independent decoding of the different images.     

A distributed lightweight Redundancy aware Topology Control Protocol for wireless sensor networks

WSN consists of a large number of sensor nodes randomly deployed, and, in many cases, it is impossible to replace sensors when a node failure occurs. Thus, applications tend to deploy more nodes than necessary to cope with possible node failures and to increase the network lifetime, which leads to create some sensing and communication redundancy. However, sensors in the same region, may collect and forward the same information, which will waste more energy. In this paper, we propose a distributed Lightweight Redundancy aware Topology Control Protocol (LRTCP) for wireless sensor networks. It exploits the sensor redundancy in the same region by dividing the network into groups so that a connected backbone can be maintained by keeping a minimum of working nodes and turning off the redundant ones. LRTCP identifies equivalent nodes in terms of communication based on their redundancy degrees with respect of some eligibility rules. Simulation results indicate that, compared with existing distributed topology control algorithms, LRTCP improves network capacity and energy efficiency.     

Cameras and display systems

We first discuss the position of cameras and displays in digital television systems. It is difficult to realize these devices in digital form so cameras and displays will remain analog for some time, even after television signal processing is implemented digitally. Nevertheless, the importance of camera and display in television systems will not diminish. These devices will always be key elements in the human interface. Second, we describe the current state of the art and future trends in camera and display technology. In addition to providing an overview of the charge coupled device (CCD), we discuss the digital technologies used in a CCD camera. We also provide an overview of currently available displays-CRT's, flat panel displays, projection displays, and head-mounted displays (HMD's)-and discuss future possible lines of research. Finally, we discuss camera and display technology as applied to digital television systems, including the use of these devices in a multimedia environment     

Leveraging data fusion to improve barrier coverage in wireless sensor networks

Intruder detection and border surveillance are amongst the most promising applications of wireless sensor networks. Barrier coverage formulates these problems as constructing barriers in a long-thin region to detect intruders that cross the region. Existing studies on this topic are not only based on simplistic binary sensing model but also neglect the collaboration employed in many systems. In this paper, we propose a solution which exploits the collaboration of sensors to improve the performance of barrier coverage under probabilistic sensing model. First, the network width requirement, the sensor density and the number of barriers are derived under data fusion model when sensors are randomly distributed. Then, we present an efficient algorithm to construct barriers with a small number of sensors. The theoretical comparison shows that our solution can greatly improve barrier coverage via collaboration of sensors. We also conduct extensive simulations to demonstrate the effectiveness of our solution.     

Collaborative sensing in a distributed PTZ camera network

The performance of dynamic scene algorithms often suffers because of the inability to effectively acquire features on the targets, particularly when they are distributed over a wide field of view. In this paper, we propose an integrated analysis and control framework for a pan, tilt, zoom (PTZ) camera network in order to maximize various scene understanding performance criteria (e.g., tracking accuracy, best shot, and image resolution) through dynamic camera-to-target assignment and efficient feature acquisition. Moreover, we consider the situation where processing is distributed across the network since it is often unrealistic to have all the image data at a central location. In such situations, the cameras, although autonomous, must collaborate among themselves because each camera's PTZ parameter entails constraints on the others. Motivated by recent work in cooperative control of sensor networks, we propose a distributed optimization strategy, which can be modeled as a game involving the cameras and targets. The cameras gain by reducing the error covariance of the tracked targets or through higher resolution feature acquisition, which, however, comes at the risk of losing the dynamic target. Through the optimization of this reward-versus-risk tradeoff, we are able to control the PTZ parameters of the cameras and assign them to targets dynamically. The tracks, upon which the control algorithm is dependent, are obtained through a consensus estimation algorithm whereby cameras can arrive at a consensus on the state of each target through a negotiation strategy. We analyze the performance of this collaborative sensing strategy in active camera networks in a simulation environment, as well as a real-life camera network.     

地面无线数字电视技术方案探讨

地面无线数字电视系统是有线电视线路无法达到的区域覆盖方式的一种,其技术方案也有不同,系统建成后应可以提供标清电视业务、数字声音广播业务、多媒体广播和数据服务业务等。建设的方案要能尽可能地利用原有的各种资源,尽可能地缩减成本,设计方案是按照安徽广电信息网络股份有限公司的网络架构进行设计的。     

Looking to build a model world: automatic construction of staticobject models using computer vision

Interest in virtual reality and multimedia has provided a great impetus to the development of automatic techniques for building graphical CAD/CAM models of objects and environments by sensing reality itself. The learning of models in this way is essential, particularly in terms of production times and attaining the required high fidelity needed for many applications. Research has produced techniques for extracting full 3D shape models using a variety of sensors and a spectrum of techniques. These include the use of static video cameras, mobile video cameras (e.g. walk through video), multiple camera platforms and/or specialist active range sensors (typically based on laser striping or sonar). This paper introduces the principles and methodologies underlying several of these methods and presents algorithms and examples from systems representative of three major approaches: models from silhouettes, models from active range sensors and, finally, models from passive uncalibrated video sequences     

Object Detection, Tracking and Recognition for Multiple Smart Cameras

Video cameras are among the most commonly used sensors in a large number of applications, ranging from surveillance to smart rooms for videoconferencing. There is a need to develop algorithms for tasks such as detection, tracking, and recognition of objects, specifically using distributed networks of cameras. The projective nature of imaging sensors provides ample challenges for data association across cameras. We first discuss the nature of these challenges in the context of visual sensor networks. Then, we show how real-world constraints can be favorably exploited in order to tackle these challenges. Examples of real-world constraints are a) the presence of a world plane, b) the presence of a three-dimiensional scene model, c) consistency of motion across cameras, and d) color and texture properties. In this regard, the main focus of this paper is towards highlighting the efficient use of the geometric constraints induced by the imaging devices to derive distributed algorithms for target detection, tracking, and recognition. Our discussions are supported by several examples drawn from real applications. Lastly, we also describe several potential research problems that remain to be addressed.      

Design and implementation of adaptive WLAN mesh networks for video surveillance

This paper presents a novel design and practical experiments of adaptive wireless mesh networks based on 802.11 based Wireless Local Area Networks for supporting public video surveillance. A network of video cameras and sensors can be equipped with wireless communication modules to form wireless surveillance at only a small expense of cost and labor. However, large and redundant multimedia data transmitted through the wireless medium pose challenging problems such as decrease in Quality of Service (QoS) and system reliability. To support seamless transmission of surveillance data through wireless means, we propose a wireless surveillance network design based on the protocols and functions of IEEE 802.11 mesh standard. One of the key functions of our adaptive mesh network is the “Multi-Gateway Routing with Congestion Avoidance”, which provides enhanced QoS support via adaptive congestion control. Network congestion is predicted in a distributed manner and amounts of data traffic transmitted to the congested path are redirected to multiple gateways. Redirection of traffic flows are made in such a way to provide quicker transmission for more time critical packets. Experimental studies via practical testbed implementation and simulation via NS-3 are conducted to prove the superiority of our proposed scheme.     

融合热释电红外传感器与视频监控器的多目标跟踪算法

现有基于热释电红外传感器的多目标跟踪系统在目标之间距离较近或者轨迹相交的情况下存在着误差较大的缺点.针对此缺点,提出了一种新型的基于热释电红外传感器与视频监测器协同工作的多目标跟踪方案.该方案可以充分利用两种传感器的优势,弥补在目标跟踪中的不足.算法采用最小二乘法利用热释电信息进行定位,并通过从图像或热释电传感器信号的幅频特性中提取特征信息来校正联合概率数据关联算法的关联矩阵,有效避免了错误关联.实验表明,该方案在多目标交叉情况下跟踪误差仅为其它算法的八分之一到四分之一.     

低维流形约束下的事件相机去噪算法

本文主要提出一个新的基于流形约束的事件相机去噪算法。事件相机是一类新型的视觉传感器,以高时间分辨率（微秒）感知场景亮度变化,同时输出具有像素位置、时间及极性的事件流。事件相机在传输亮度变化的同时受到噪声的干扰,带噪的事件流会对后续的应用造成不利的影响。为了解决该问题,本文假设事件分布在高维空间中的低维流形上,利用事件点间相似信息建立图模型以近似流形结构,结合图的流形平滑约束,实现事件流去噪。该算法首次将基于图的流形约束引入事件去噪问题中并且直接处理连续的事件序列。仿真实验和真实数据结果证明了事件去噪算法的有效性。      

Impact of Interference on Coverage in Wireless Sensor Networks

The quality of surveillance is dependent on the sensing coverage of a wireless sensor network. In the present paper, we examine how interference affects the coverage of a wireless sensor network. The coverage fraction and required number of sensors for randomly deployed and well-planned deployed wireless sensor networks in the presence of interferers are computed. The required number of sensors to achieve higher level of coverage increases drastically for randomly distributed sensor nodes where the interference effect is high. In the case of well-planned distributed sensor network, required sensors increases linearly as interference effects become more pronounced. Algorithms for computing the required number of sensors to obtain the desired level of coverage in the presence of non-uniform interference is presented. The simulation results suggest that the coverage per subregion and coverage per sensor approaches towards, the improvement achieved is constant. The sensor saving ratio is independent of the level of the desired coverage provided the coverage per subregion is larger than or equal to the coverage per sensor.     

Distributed Medium Access Control Next-Generation CDMA Wireless Networks

The next-generation wireless networks are expected to have a simple infrastructure with distributed control. In this article, we consider a generic distributed network model for future wireless multimedia communications with a code-division multiple access (CDMA) air interface. For the medium access control (MAC) of the network model, we provide an overview of recent research efforts on distributed code assignment and interference control and identify their limitations when applied in next-generation wireless networks supporting multimedia traffic. We also propose a novel distributed MAC scheme to address these limitations, where active receivers determine whether a candidate transmitter should transmit its traffic or defer its transmission to a later time. Simulation results are given to demonstrate the effectiveness of the proposed distributed MAC scheme.