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Signal processing / Simultaneous localization and mapping / Kalman filter / Burglar alarm / Wireless sensor network / Motion detector / Image noise / Passive infrared sensor / Sensors / Security / Technology


Sensitivity Analysis for Intruder Tracking Using Particle Filtering and a Network of Binary Sensors Enrique G. Ortiz Jeremy Schiff
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Document Date: 2006-08-30 11:31:57


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File Size: 847,80 KB

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Las Vegas / Edmonton / New York / /

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Pearson / MIT Press / Panasonic / ACM Press / Intel / /

Country

Japan / United States / Canada / /

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USD / /

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Facility

EECS University of Central Florida Orland / Art gallery / Simon Fraser University / University of California / EECS University of California / /

IndustryTerm

wireless sensors / ubiquitous computing / on-line non-linear/non-gaussian bayesian tracking / wireless network / camera systems / real-time tracking / nonlinear systems / Online searching / security systems / computing / remote low-cost position sensing infrastructure / wireless networks / /

Organization

IEOR / School of Computing Science / MIT / EECS University / University of Central Florida / University of California / Berkeley / Binary Sensors Enrique G. Ortiz Jeremy Schiff Ken Goldberg School / Simon Fraser University / American Society of Mechanical Engineers / Pattern Analysis and Machine Intelligence / EECS Department / /

Person

Y.P. Li / M.H. Ang Jr. / Shu Lu / D. Hsu / S. Pankanti / T. Bandyopadhyay / Particle Filtering / Ken Goldberg / Jeremy Schiff / Jeremy Schiff Ken / /

Position

representative / probabilistic model for the sensor / probabilistic tracking model / /

Product

Sampling Importance Resampling (SIR) Filter / Franklin / /

ProgrammingLanguage

FL / /

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Nevada / California / New York / /

PublishedMedium

IEEE Transactions on Pattern Analysis and Machine Intelligence / /

Region

Central Florida / /

Technology

Machine Vision / artificial intelligence / GPS / simulation / Approximate and distributed algorithms / 2.4 GHz processor / /

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