58 research outputs found

    On Achieving Diversity in the Presence of Outliers in Participatory Camera Sensor Networks

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    This paper addresses the problem of collection and delivery of a representative subset of pictures, in participatory camera networks, to maximize coverage when a significant portion of the pictures may be redundant or irrelevant. Consider, for example, a rescue mission where volunteers and survivors of a large-scale disaster scout a wide area to capture pictures of damage in distressed neighborhoods, using handheld cameras, and report them to a rescue station. In this participatory camera network, a significant amount of pictures may be redundant (i.e., similar pictures may be reported by many) or irrelevant (i.e., may not document an event of interest). Given this pool of pictures, we aim to build a protocol to store and deliver a smaller subset of pictures, among all those taken, that minimizes redundancy and eliminates irrelevant objects and outliers. While previous work addressed removal of redundancy alone, doing so in the presence of outliers is tricky, because outliers, by their very nature, are different from other objects, causing redundancy minimizing algorithms to favor their inclusion, which is at odds with the goal of finding a representative subset. To eliminate both outliers and redundancy at the same time, two seemingly opposite objectives must be met together. The contribution of this paper lies in a new prioritization technique (and its in-network implementation) that minimizes redundancy among delivered pictures, while also reducing outliers.unpublishedis peer reviewe

    A visual sensor network for object recognition: Testbed realization

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    This work describes the implementation of an object recognition service on top of energy and resource-constrained hardware. A complete pipeline for object recognition based on the BRISK visual features is implemented on Intel Imote2 sensor devices. The reference implementation is used to assess the performance of the object recognition pipeline in terms of processing time and recognition accuracy

    Coding mode decision algorithm for binary descriptor coding

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    In visual sensor networks, local feature descriptors can be computed at the sensing nodes, which work collaboratively on the data obtained to make an efficient visual analysis. In fact, with a minimal amount of computational effort, the detection and extraction of local features, such as binary descriptors, can provide a reliable and compact image representation. In this paper, it is proposed to extract and code binary descriptors to meet the energy and bandwidth constraints at each sensing node. The major contribution is a binary descriptor coding technique that exploits the correlation using two different coding modes: Intra, which exploits the correlation between the elements that compose a descriptor; and Inter, which exploits the correlation between descriptors of the same image. The experimental results show bitrate savings up to 35% without any impact in the performance efficiency of the image retrieval task. © 2014 EURASIP

    FPGA-based smart camera mote for pervasive wireless network

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    International audienceSmart camera networks raise challenging issues in many fields of research, including vision processing, communication protocols, distributed algorithms or power management. The ever increasing resolution of image sensors entails huge amounts of data, far exceeding the bandwidth of current networks and thus forcing smart camera nodes to process raw data into useful information. Consequently, on-board processing has become a key issue for the expansion of such networked systems. In this context, FPGA-based platforms, supporting massive, fine grain data parallelism, offer large opportunities. Besides, the concept of a middleware, providing services for networking, data transfer, dynamic loading or hardware abstraction, has emerged as a means of harnessing the hardware and software complexity of smart camera nodes. In this paper, we prospect the development of a new kind of smart cameras, wherein FPGAs provide high performance processing and general purpose processors support middleware services. In this approach, FPGA devices can be reconfigured at run-time through the network both from explicit user request and transparent middleware decision. An embedded real-time operating system is in charge of the communication layer, and thus can autonomously decide to use a part of the FPGA as an available processing resource. The classical programmability issue, a significant obstacle when dealing with FPGAs, is addressed by resorting to a domain specific high-level programming language (CAPH) for describing operations to be implemented on FPGAs

    Vision Graph Construction in Wireless Multimedia Sensor Networks

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    In Wireless multimedia sensor networks (WMSNs), the camera nodes connected in the vision graph share overlapped field of views (FOVs) and they depend on the densely deployed relay nodes in the communication network graph to communicate with each other. Given a uniformly deployed camera sensor network with relay nodes, the problem is to find the number of hops for the vision-graph-neighbor-searching messages to construct the vision graph in an energy efficient way. In this paper, mathematical models are developed to analyze the FOV overlap of the camera nodes and the multi-hop communications in two dimensional topologies, which are utilized to analyze the relation between vision graph construction and maximum hop count. In addition, simulations are conducted to verify the models

    Improving target localization accuracy of wireless visual sensor networks

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    This paper discusses the target localization problem of wireless visual sensor networks. Specifically, each node with a low-resolution camera extracts multiple feature points to represent the target at the sensor node level. A statistical method of merging the position information of different sensor nodes to select the most correlated feature point pair at the base station is presented. This method releases the influence of the accuracy of target extraction on the accuracy of target localization in universal coordinate system. Simulations show that, compared with other relative approach, our proposed method can generate more desirable target localization's accuracy, and it has a better trade-off between camera node usage and localization accuracy

    Experimental evaluation of a video streaming system for Wireless Multimedia Sensor Networks

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    Wireless Multimedia Sensor Networks (WMSNs) are recently emerging as an extension to traditional scalar wireless sensor networks, with the distinctive feature of supporting the acquisition and delivery of multimedia content such as audio, images and video. In this paper, a complete framework is proposed and developed for streaming video flows in WMSNs. Such framework is designed in a cross-layer fashion with three main building blocks: (i) a hybrid DPCM/DCT encoder; (ii) a congestion control mechanism and (iii) a selective priority automatic request mechanism at the MAC layer. The system has been implemented on the IntelMote2 platform operated by TinyOS and thoroughly evaluated through testbed experiments on multi-hop WMSNs. The source code of the whole system is publicly available to enable reproducible research. © 2011 IEEE

    Mobile objects and sensors within a video surveillance system: Spatio-temporal model and queries

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    International audienceThe videos recorded by video surveillance systems represent a key element in a police inquiry. Based on a spatio-temporal query specified by a victim, (e.g., the trajectory of the victim before and after the aggression) the human operators select the cameras that could contain relevant information and analyse the corresponding video contents. This task becomes cumbersome because of the huge volume of video contents and the cameras' mobility. This paper presents an approach, which assists the operator in his task and reduces the research space. We propose to model the cameras' network (fixed and mobile cameras) on top of the city's transportation network. We consider the video surveillance system as a multilayer geographic information system, where the cameras are situated into a distinct layer, which is added on top of the other layers (e.g., roads, transport) and is related to them by the location. The model is implemented in a spatio-temporal database. Our final goal is that based on a spatio-temporal query to automatically extract the list of cameras (fixed and mobile) concerned by the query. We propose to include this automatically computed relative position of the cameras as an extension of the standard ISO 22311

    Optimized Visual Internet of Things in Video Processing for Video Streaming

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    The global expansion of the Visual Internet of Things (VIoT) has enabled various new applications during the last decade through the interconnection of a wide range of devices and sensors.Frame freezing and buffering are the major artefacts in broad area of multimedia networking applications occurring due to significant packet loss and network congestion. Numerous studies have been carried out in order to understand the impact of packet loss on QoE for a wide range of applications. This paper improves the video streaming quality by using the proposed framework Lossy Video Transmission (LVT)  for simulating the effect of network congestion on the performance of  encrypted static images sent over wireless sensor networks.The simulations are intended for analysing video quality and determining packet drop resilience during video conversations.The assessment of emerging trends in quality measurement, including picture preference, visual attention, and audio visual quality is checked. To appropriately quantify the video quality loss caused by the encoding system, various encoders compress video sequences at various data rates.Simulation results for different QoE metrics with respect to user developed videos have been demonstrated which outperforms the existing metrics

    Energy Efficiency of Image Transmission in Embedded Linux based Wireless Visual Sensor Network

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    Wireless Visual Sensor Network (WVSN) is a system that consists of visual sensor nodes with an embedded processor. WVSN devices have limited resources of energy, computation capability, memory, and bandwidth. Due to these limitations the implementation of WVSN for large multimedia data, such as images, become a challenging task. Therefore, it is required compressed images prior to transmission. In addition to the limited resources, the system implementation strongly affects the efficiency of the working system. The main contribution of this research is to offer a technical solution of simpler image compression on the WVSN platform. JPEG 2000 is investigated as an alternative compression method to reduce the size of data transfer on WVSN using Embedded Linux as its operating system. Compressed images are transferred to a receiver on communication of IEEE 802.15.4.. This paper shows that the energy consumption for compression and transmission will reduce to only 10.48%, 13.60%, and 17.11% compared to raw image. BER will significantly reduce by implementing image compression. Therefore, it is demonstrated that this model significantly increases energy efficiency, memory utilization efficiency, and data transfer time with acceptable PSNR, compared to uncompressed images
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