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检索条件"任意字段=Conference on Sensor Fusion - Architectures, Algorithms, and Applications"

共 2092 条记录，以下是171-180 订阅

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Real-time tracking and fast retrieval of persons in multiple surveillance cameras of a shopping mall

Real-time tracking and fast retrieval of persons in multiple...

引用

conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Bouma, Henri Baan, Jan Landsmeer, Sander Kruszynski, Chris van Antwerpen, Gert Dijk, Judith TNO POB 96864 NL-2509 JG The Hague Netherlands

ISBN: (纸本)9780819495471

The capability to track individuals in CCTV cameras is important for e.g. surveillance applications at large areas such as train stations, airports and shopping centers. However, it is laborious to track and trace people over multiple cameras. In this paper, we present a system for real-time tracking and fast interactive retrieval of persons in video streams from multiple static surveillance cameras. This system is demonstrated in a shopping mall, where the cameras are positioned without overlapping fields-of-view and have different lighting conditions. The results show that the system allows an operator to find the origin or destination of a person more efficiently. The misses are reduced with 37%, which is a significant improvement.

关键词： Surveillance tracking CCTV person re-identification multi-sensor fusion

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Scene recognition with audio-visual sensor fusion

Scene recognition with audio-visual sensor fusion

引用

conference on Multisensor, Multisource Information fusion

作者： Devicharan, D Mehrotra, KG Mohan, CK Varshney, PK Zuo, L Syracuse Univ Dept EECS Syracuse NY 13244 USA

ISBN: (纸本)0819457981

Several surveillance applications are characterized by the ability to gather information about the scene from more than one sensor modality, and heterogeneous sensor data must then be fused by the decision-maker. hi this paper, we discuss the issues relevant to developing a model for fusion of information from audio and visual sensors, and present a framework to enhance decision-making capabilities. In particular, our methodology focuses on the issues of temporal reasoning, uncertainty representations, and coupling between features inferred from data streams coming from different sensors. We propose a conditional probability-based representation for uncertainty, along with fuzzy rules to assist decision-making, and a matrix representation of the coupling between sensor data streams. We also develop a fusion algorithm that utilizes these representations.

关键词： multimodal sensor fusion scene recognition activity detection audio and visual surveillance

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Robust speech separation using visually constructed speech signals

Robust speech separation using visually constructed speech s...

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conference on sensor fusion - architectures, algorithms, and applications VI

作者： Aarabi, P Khameneh, NH Univ Toronto Dept Elect & Comp Engn Toronto ON M5M 3G4 Canada

ISBN: (纸本)0819444812

A technique to virtually recreate speech signals entirely from the visual lip motions of a speaker is proposed. By using six geometric parameters of the lips obtained from the Tulips1 database, a virtual speech signal is recreated by using a 3.6s audiovisual training segment as a basis for the recreation. It is shown that the virtual speech signal has an envelope that is directly related to the envelope of the original acoustic signal. This visual signal envelope reconstruction is then used as a basis for robust speech separation where all the visual parameters of the different speakers are available. It is shown that, unlike previous signal separation techniques, which required an ideal mixture of independent signals, the mixture coefficients can be very accurately estimated using the proposed technique in even non-ideal situations.

关键词： audiovisual information fusion blind speech separation independent component analysis audiovisual signal separation robust speech recognition

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Revisions to the JDL data fusion model

Revisions to the JDL data fusion model

引用

conference on sensor fusion - architectures, algorithms, and applications III

作者： Steinberg, AN Bowman, CL White, FE ERIM Int Inc Arlington VA 22209 USA

ISBN: (纸本)0819431931

The Data fusion Model maintained by the Joint Directors of Laboratories (JDL) Data fusion Group is the most widely-used method for categorizing data fusion-related functions. This paper discusses the current effort to revise and expand this model to facilitate the cost-effective development, acquisition, integration and operation of multi-sensor/multi-source systems. Data fusion involves combining information - in the broadest sense - to estimate or predict the state of some aspect of the universe. These may be represented in terms of attributive and relational states. If the job is to estimate the state of a people (or any other sentient beings), it can be useful to include consideration of informational and perceptual stares in addition to the physical state. Developing cost-effective multi-source information systems requires a method for specifying data fusion processing and control functions, interfaces, and associated databases. The lack of common engineering standards for data fusion systems has been a major impediment to integration and re-use of available technology: current developments do nor lend themselves to objective evaluation, comparison or re-use. This paper reports on proposed revisions and expansions of the JDL Data fusion model to remedy some of these deficiencies. This involves broadening the functional model and related taxonomy beyond the original military focus, and integrating the Data fusion Tree Architecture model for system description, design and development.

关键词： Data fusion Data modeling Systems modeling Standards development Data processing sensors Algorithm development Data analysis Systems engineering Signal detection

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Proceedings of SPIE: Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2005

Proceedings of SPIE: Multisensor, Multisource Information Fu...

引用

Multisensor, Multisource Information fusion: Architecture, algorithms, and applications 2005

The proceedings contain 35 papers from the conference on Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2005. Topics discussed include: reduced data projection slice image fusion using principal component analysis;real-time implementation of image alignment and fusion;image fusion with the hybrid evolutionary algorithm and response analysis;a perceptual quality metric for image fusion based on regional information;multispectral sensor fusion using the projection-slice theorem;a situation awareness model applied to multiple domains;hybrid framework for fusion 2+ in multi-multi air engagement;and product-based multiresolution image fusion.

关键词： sensor data fusion

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The application of Dempster-Shafer theory for landmine detection

The application of Dempster-Shafer theory for landmine detec...

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conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Mudigonda, NR Kacelenga, R Erickson, D Gen Dynam Canada Ltd Calgary AB T2E 8P2 Canada

ISBN: (纸本)0819449598

This paper explores the concepts of multisensor data fusion based on the Dempster-Shafer (DS) evidential theory in order to achieve a mine versus false-alarm (FA) classification of landmine targets. Initially, a decision-level DS algorithm is proposed to combine the evidence from multiple sensors of the landmine detection system developed by the General Dynamics Canada Limited (GD Canada). Subsequently, a feature-level DS fusion algorithm is employed to operate on a set of features reported by the ground penetrating radar (GPR) sensor of the system. The data used in the present study was acquired from the Aberdeen Proving Grounds (APG) test site in USA as part of the Ground Standoff Mine Detection System (GSTAMIDS) trials. The proposed decision-level DS algorithm yielded a probability of detection (Pd) of 92.53% at a false-alarm rate (FAR) value of 0.0697 FAs/m(2). The Pd and the FAR performance results achieved by using the decision-level DS algorithm are comparable with the results obtained using three other decision-level fusion algorithms that were previously developed by GD, Canada based on heuristic, Bayesian inference, and Voting fusion concepts. On the other hand, the feature-level DS fusion, when tested with the information presented by the GPR sensor only, resulted in a higher Pd value of 78.54% as compared to the corresponding result of 61.43% obtained by using the heuristic algorithm. The GPR sensor is one of the three scanning sensors present on the system.

关键词： landmine detection multisensor data fusion Dempster-Shafer theory Bayesian theory voting fusion

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Use of multi sensor fusion technology to meet the challenges of emerging EO & RF threats to a combat aircraft

Use of multi sensor fusion technology to meet the challenges...

引用

conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Shukla, AK Parthasarathy, T Rao, PNAP Govt India Minist Def Aeronaut Dev Agcy Bangalore 560017 Karnataka India

ISBN: (纸本)0819449598

The pilot on-board a combat aircraft encounters during any mission a dynamically varying threat environment of diverse EO and RF threats. Different sensors are carried on-board the aircraft to combat these threats. However, these sensors have their own limitations and no single sensor is able to perform in all kinds of situations. In addition, the technological advances in the threat scenario - in terms of higher speeds, small signatures and multimode guidance - and increased complex threats in the battlefield leading to generation of large amount of data input to the pilot make his decision making task very difficult due to increased workload. These challenges can be efficiently handled by deployment of a system on-board the aircraft with a comprehensive goal of autonomous target detection and tracking, situation and threat assessment and decision making based on multi-sensor data fusion techniques. In this paper, major emerging EO and RF threats for a combat aircraft and some important EO and RF sensors on-board the aircraft have been discussed. A design approach for the development of a multi-sensor data fusion system for a combat aircraft to provide better threat assessment than that provided by any single stand alone sensor has also been presented.

关键词： Multi-sensor Data fusion Electro-Optical (EO) Radio Frequency (RF) Moving Target Image (MTTM) Multiple Hypothesis Tracking (MHT) Probabilistic Data Association (PDA)

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Pulse coupled neural network sensor fusion

Pulse coupled neural network sensor fusion

引用

conference on sensor fusion - architectures, algorithms, and applications II

作者： Johnson, JL Schamschula, MP Inguva, R Caulfield, HJ USA AMCOM Redstone Arsenal AL 35809 USA

ISBN: (纸本)0819428256

Perception is assisted by sensed impressions of the outside world but not determined by them. The primary organ of perception is the brain and, in particular, the cortex. With that in mind, we have sought to see how a computer-modeled cortex - the PCNN or Pulse Coupled Neural Network - performs as a sensor fusing element. In essence, the PCNN is comprised of an array of integrate-and-fire neurons with one neuron for each input pixel. In such a system, the neurons corresponding to bright pixels reach firing threshold faster than the neurons corresponding to duller pixels. Thus, firing rate is proportional to brightness. In PCNNs, when a neuron fires it sends some of the resulting signal to its neighbors. This linking can cause a near-threshold neuron to fire earlier than it would have otherwise. This leads to synchronization of the pulses across large regions of the image. We can simplify the three-dimensional PCNN output by integrating out the time dimension. Over a long enough time interval, the resulting two-dimensional (x,y) pattern IS the input image. The PCNN has taken it apart and put it back together again. The shorter-term time integrals are interesting in themselves and will be commented upon in the paper. The main thrust of this paper is the use of multiple PCNNs mutually coupled in various ways to assemble a single two-dimensional pattern or fused image. Results of experiments on PCNN image fusion and an evaluation of its advantages are our primary objectives.

关键词： Image fusion Neurons sensors Data modeling RGB color model Neural networks Modulation Pulse generators sensor fusion Image processing

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Process performance monitoring by using information fusion in a high volume consumer electronics manufacturing process.

Process performance monitoring by using information fusion i...

引用

conference on sensor fusion: architectures, algorithms, and applications IV

作者： Asp, S Wide, P Univ Orebro AASS Res Grp Dept Technol & Sci Orebro Sweden

ISBN: (纸本)0819436771

As production volumes continue to increase and the global market for consumer electronics is getting fiercer, the need for a reliable and essentially fault-free production process is becoming a necessity to survive. The manufacturing processes of today are highly complex and the increasing amount of process data is making it hard to unravel the useful information extracted from a huge data set. In general, high volume manufacturing processes often increase the need for more sensor data which require new approaches of measuring technologies in order to increase the overall process knowledge. However, the analysis of huge data sets of process information has become more important, e.g. how do we extract the information features and fuse different information in order to optimize a process and reduce the overall data amount. A process performance monitoring application for a high volume consumer electronics manufacturing process, by using multivariate information fusion techniques, has been developed. The purpose of the monitoring system is to identify test stations deviating in measurement values from other test stations and to provide early warning and identification of important process related disturbances, malfunctions or faults by extracting information by sensor measurements and by using knowledge about the process.

关键词： process performance monitoring high volume manufacturing information fusion multivariable analysis SPC MSPC

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An unified approach to the fusion of imperfect data?

An unified approach to the fusion of imperfect data?

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conference on sensor fusion - architectures, algorithms, and applications VI

作者： Florea, MC Jousselme, AL Grenier, D Bossé, É Univ Laval Dept Genie Elect LRTS Ste Foy PQ G1K 7P4 Canada

ISBN: (纸本)0819444812

For several years, researchers have explored the unification of the theories enabling the fusion of imperfect data and have finally considered two frameworks: the random sets and the conditional events algebra. Traditionally, the information is modeled and fused in one of the known theories: bayesian, fuzzy sets, possibilistic, evidential, or rough sets... Previous work has shown what kind of imperfect data these theories can best deal with. So, depending on the quality of the available information (uncertain, vague, imprecise,...), one particular theory seems to be the preferred choice for fusion. However, in a typical application, the variety of sources provides different kinds of imperfect data. The classical approach is then to model and fuse the incoming data in a single theory being previously chosen. In this paper, we first introduce the various kinds of imperfect data and then the theories that can be used to cope with the imperfection. We also present the existing relationships between them and detail the most important properties for each theory. We finally propose the random sets theory as a possible framework for unification, and thus show how the individual theories can fit in this framework.

关键词： imperfect data data fusion random sets

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