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检索条件"任意字段=Sensor Fusion: Architectures, Algorithms and Applications II"

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Field-based data collection techniques for the evaluation of information fusion systems

Field-based data collection techniques for the evaluation of...

引用

Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2009

作者： Antonishek, Brian Weiss, Brian A. Schlenoff, Craig National Institute of Standards and Technology 100 Bureau Drive Gaithersburg MD 20899 United States

ISBN: (纸本)9780819476111

In order to effectively evaluate information fusion systems or emerging technologies, it is critical to quickly, efficient, and accurately collect functional and observational data about such systems. One of the best ways to test a system's capabilities is to have an end user operate it in controlled but realistic field-based situations. Evaluation data of the systems' performance as well as observational data of the user's interactions can then be collected and analyzed. This analysis often gives insight into how the system may perform in the intended environment and of any potential areas for improvement. One common method for collection of this data involves an evaluator/observer generating hand-written notes, comments, and sketches. This often proves to be inefficient in complex sensor technology field-based evaluation environments. Personnel at the National Institute of Standards and Technology (NIST) have been tasked with collecting such evaluation data for emerging soldier-worn sensor systems. Lessons learned from the on-going development of efficient field-based evaluation data collection techniques will be discussed. The most recent evaluation data collection using a personal digital assistant (PDA)-style system and details of its use during an evaluation of a multi-team study will also be described. © 2009 SPIE.

关键词： Personal digital assistants

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Centralized fusion for Fast People Detection in Dense Environment

Centralized Fusion for Fast People Detection in Dense Enviro...

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IEEE International Conference on Robotics and Automation

作者： Gate, Gwennael Breheret, Amaury Nashashibi, Fawzi Mines ParisTech Robot Lab 60 Blvd St Michel F-75273 Paris France Inst Natl Rech Informat & Automat IMARA Team Mines ParisTech Robot Lab F-78153 Le Chesnay France

ISBN: (纸本)9781424427888

Human beings do not have well defined shapes neither well defined behaviors. In dense outdoor environments, they are as a consequence hard to detect and algorithms based on a single sensor tend to produce lot of wrong detections. Moreover, many applications require algorithms that work very fast on CPU limited mobile architectures while remaining able to detect, track and classify objects as people with a very high precision. We present an algorithm based on the contribution of a range finder and a vision based algorithm that addresses these three constraints: efficiency, velocity and robustness and that we believe is scalable to a large variety of applications.

关键词： People detection Target tracking Boosting Data fusion

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Resource-Optimized Quality-Assured Ambiguous Context Mediation in Pervasive Environments

Resource-Optimized Quality-Assured Ambiguous Context Mediati...

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6th Int ICST Conf on Heterogeneous Networking for Quality, Reliability, Security and Robustness/3rd Int Workshop on Adv architectures and algorithms for Internet Delivery and Appl

作者： Roy, Nirmalya Julien, Christine Das, Sajal K. Univ Texas Austin Dept Elect & Comp Engn Austin TX 78712 USA Univ Texas Arlington Dept Comp Sci & Engn Arlington TX 76019 USA

ISBN: (纸本)9783642106248

Pervasive computing applications envision sensor rich computing and networking environments that can capture various types of contexts of inhabitants of the environment, such as their locations, activities, vital signs, and environmental measures. Such context information is useful in a variety of applications, for example to manage health information to promote independent living in "aging-in-place" scenarios. In reality, both sensed and interpreted contexts are often ambiguous, leading to potentially dangerous decisions if not properly handled. Thus, a significant challenge facing the development of realistic and deployable context-aware services for pervasive computing applications is the ability to deal with these ambiguous contexts. In this paper, we propose a resource optimized quality assured context mediation framework for resource constrained sensor networks based on efficient context-aware data fusion and information theoretic sensor parameter selection for optimal state estimation. The proposed framework provides a systematic approach based on dynamic Bayesian networks to derive context fragments and deal with context ambiguity or error in a probabilistic manner. Experimental results using SunSPOT sensors demonstrate the promise of this approach.

关键词： Context-awareness Ambiguous contexts Bayesian networks Multi sensor fusion Information theory SunSPOT

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Real deployment of Consensus Algorithm on Self-organized Wireless sensor Networks

Real deployment of Consensus Algorithm on Self-organized Wir...

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16th International Conference on Telecommunications (ICT)

作者： Elbhiri, Brahim Pages-Zamora, Alba Aboutajdine, Driss FSR Lab Rech Informat & Telecommun Rabat Morocco UPC Signal Processing & Commun Grp Barcelona Spain

ISBN: (纸本)9781424429363

Reaching consensus on a self-organized wireless sensor networks through totally decentralized algorithms is a topic that has attracted considerable attention. The average consensus method is the most popular algorithm used in this kind of applications. The main advantage of these approaches is that the network does not involve a fusion center to organize nodes. Using a realistic environment to check the behavior of this scheme is the major objective of this work. Moreover, this paper contributes to answer and confirm some results which are approved by theoretical works.

关键词： Wireless sensor networks

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Biologically-inspired robust and adaptive multi-sensor fusion and active control

Biologically-inspired robust and adaptive multi-sensor fusio...

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Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2009

作者： Khosla, Deepak Dow, Paul A. Huber, David J. HRL Laboratories LLC Malibu CA United States

ISBN: (纸本)9780819476111

In this paper, we describe a method and system for robust and efficient goal-oriented active control of a machine (e.g., robot) based on processing, hierarchical spatial understanding, representation and memory of multimodal sensory inputs. This work assumes that a high-level plan or goal is known a priori or is provided by an operator interface, which translates into an overall perceptual processing strategy for the machine. Its analogy to the human brain is the download of plans and decisions from the pre-frontal cortex into various perceptual working memories as a perceptual plan that then guides the sensory data collection and processing. For example, a goal might be to look for specific colored objects in a scene while also looking for specific sound sources. This paper combines three key ideas and methods into a single closed-loop active control system. (1) Use high-level plan or goal to determine and prioritize spatial locations or waypoints (targets) in multimodal sensory space;(2) collect/store information about these spatial locations at the appropriate hierarchy and representation in a spatial working memory. This includes invariant learning of these spatial representations and how to convert between them;and (3) execute actions based on ordered retrieval of these spatial locations from hierarchical spatial working memory and using the "right" level of representation that can efficiently translate into motor actions. In its most specific form, the active control is described for a vision system (such as a pantilt-zoom camera system mounted on a robotic head and neck unit) which finds and then fixates on high saliency visual objects. We also describe the approach where the goal is to turn towards and sequentially foveate on salient multimodal cues that include both visual and auditory inputs. © 2009 SPIE.

关键词： Data handling

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Multisensor information compression and reconstruction

Multisensor information compression and reconstruction

引用

Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2009

作者： Bing, Du Liang, Liu Jun, Zhang School of Electronics and Information Engineering Beihang Univ. XueYuan Road 37 Haidian District Beijing 100191 China

ISBN: (纸本)9780819476111

In this paper, we propose a method of sampled data compression and reconstruction using the theory of distributed compressed sensing for wireless sensor network, in which the correlation between the sensors is considered for joint sparsity representation, compression and reconstruction of the signals. And incoherent random projection CS matrix in each sensor is as encoding matrix to generate compressed measurements for storing, delivering and processing. The reconstruction algorithm with both acceptable complexity and precision is developed for noise corrupted measurements by fully utilizing of correlations diversity. The simulation shows that the number of measurements only slightly larger than the sparsity of the sampled sensor data is needed for successful recovery. © 2009 SPIE.

关键词： Wireless sensor networks

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An Approach for Incorporating End User Knowledge into applications of Information Extraction Classification and fusion in Institutional Eldercare

An Approach for Incorporating End User Knowledge into Applic...

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International Symposium on Parallel architectures, algorithms and Networks (ISPAN)

作者： C.-C. Hsia K. J. Liou A. P. W. Aung S. F. Foo W. Huang J. Biswas Industrial Technology Research Institute Hsinchu TW Networking Protocols Dept. Institute for Infocomm Research Singapore Computer Vision and Image Understanding Dept. Institute for Infocomm Research Singapore Networking Protocols Dept. Institute for Infocomm Research Singapore Singapore

sensor-based smart spaces have been developed to help caring of the elderly. Selection of sensors, layout of smart space, design of fusion algorithms, and knowledge of domain experts are critical to the development of a useful ICT system for caring the elderly in the institutional facilities. We apply multi-modal sensor fusion technique to improve the confidence level of our system, and leverage the knowledge of domain experts, which is stored in ontology database, to detect the sequence of events that can lead to dangerous situations.

关键词： Data mining Senior citizens Intelligent sensors sensor fusion sensor systems Algorithm design and analysis Multimodal sensors Ontologies Databases Event detection

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Centralized fusion for fast people detection in dense environment

Centralized fusion for fast people detection in dense enviro...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Gwennael Gate Amaury Breheret Fawzi Nashashibi Robotics Laboratory Mines Paris-Tech Paris France Robotics Laboratory Mines ParisTech and INRIA-IMARA team Le Chesnay France

关键词： Shape Robustness Cameras Humans Laser fusion Detection algorithms Robots Target tracking Recursive estimation Bayesian methods

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Multi-camera networks : principles and applications /

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2009年

作者： Hamid Aghajan Andrea Cavallaro [editors].

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Decision fusion in sensor Networks for Spectrum Sensing based on Likelihood Ratio Tests

Decision Fusion in Sensor Networks for Spectrum Sensing base...

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Conference on Advanced Signal Processing algorithms, architectures, and Implementantions XViiI

作者： Chung, Wei-Ho Yao, Kung Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA

ISBN: (纸本)9780819472946

sensor networks have been shown to be useful in diverse applications. One of the important applications is the collaborative detection based on multiple sensors to increase the detection performance. To exploit the spectrum vacancies in cognitive radios, we consider the collaborative spectrum sensing by sensor networks in the likelihood ratio test (LRT) frameworks. In the LRT, the sensors make individual decisions. These individual decisions are then transmitted to the fusion center to make the final decision, which provides better detection accuracy than the individual sensor decisions. We provide the lowered-bounded probability of detection (LBPD) criterion as an alternative criterion to the conventional Neyman-Pearson (NP) criterion. In the LBPD criterion, the detector pursues the minimization of the probability of false alarm while maintaining the probability of detection above the pre-defined value. In cognitive radios, the LBPD criterion limits the probabilities of channel conflicts to the primary users. Under the NP and LBPD criteria, we provide explicit algorithms to solve the LRT fusion rules, the probability of false alarm, and the probability of detection for the fusion center. The fusion rules generated by the algorithms are optimal under the specified criteria. In the spectrum sensing, the fading channels influence the detection accuracies. We investigate the single-sensor detection and collaborative detections of multiple sensors under various fading channels, and derive testing statistics of the LRT with known fading statistics.

关键词： sensor networks cognitive radio lower-bounded probability of detection criterion Neyman-Pearson criterion decision fusion

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