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Artificial intelligence / Science / Bioinformatics / Hidden Markov model / Statistical models / Activity recognition / Fisher kernel / Support vector machine / Generative model / Statistics / Machine learning / Statistical classification


Abnormal Activity Recognition based on HDP-HMM Models
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Document Date: 2009-07-14 20:11:24

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City

HDPHMM / /

Company

Autonomous Systems / Multiagent Systems / State Key Laboratory / Information Engineering Laboratory / Dynamic Bayesian Networks / Markov / /

Country

Australia / /

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Facility

Building One-Class SVM / Hong Kong University of Science / Nanjing University / CSIRO ICT Centre / /

IndustryTerm

baseline algorithm / machine learning algorithms / data mining areas / pervasive computing researchers / abnormal activity recognition algorithms / abnormality detection algorithm / real-world applications / baseline algorithms / sensor networks / efficient algorithm / ensemble learning algorithm / activity recognition algorithms / ubiquitous computing research / ai plan recognition technology / online inference algorithms / learning-based activity recognition algorithms / abnormal activity recognition algorithm / probabilistic plan recognition algorithm / real-world activity recognition systems / /

Organization

American Statistical Association / CSIRO ICT Centre / MIT / Qiang Yanga Department of Computer Science and Engineering / Hong Kong University of Science and Technology / Nanjing University / NEC China Lab / Artificial Intelligence / /

Person

Colleen E. McCarthy / Jaideep Srivastava / Cheryl Orosz / Karen L. Myers / Jonathan Lester / Svetha Venkatesh / Samy Bengio / Peter Jarvis / Aleksandar Lazarevic / John D. Lafferty / Martha E. Pollack / Nicky Kern / Tanzeem Choudhury / Michael I. Jordan / Pallavi Kaushik / Hao Hua / Jennifer Beaudin / Manuela M. Veloso / Henry A. Kautz / David Haussler / Teresa F. Lunt / Randy Rockinson / Hua Liu / Andrew P. Bradley / Bart Peintner / Yang Gao / Xianxing Zhang / John Maraist / Derek Hao Hu / Jie Yinc / Christopher W. Geib / Xian-Xing Zhangb / Jie Yin / Douglas L. Vail / Stephen S. Intille / Dieter Fox / Iain McCowan / Jason Nawyn / Blake Hannaford / Qiang Yang / Tommi Jaakkola / Robert P. Goldman / Lin Liao / Aysel Ozgur / Yee Whye Teh / Vipin Kumar / Sailesh Ramakrishnan / Thi V. Duong / Daniel Gatica-Perez / Ioannis Tsamardinos / Dinh Q. Phung / Hung Hai Bui / Emmanuel Munguia Tapia / Junfeng Pan / Dong Zhang / Kent Larson / Dirk Colbry / Laura E. Brown / Gaetano Borriello / Levent Ert¨oz / Kernel / David M. Blei / Matthew J. Beal / Vincent Wenchen Zhenga / Qiang Yanga / /

Position

incorporating Fisher / model for abnormal characteristics / author / OCSVM model / Fisher information matrix / Fisher / representative / /

Product

One-Class SVMs / Fisher / /

PublishedMedium

Journal of The American Statistical Association / /

Technology

abnormal activity recognition algorithms / machine learning algorithms / baseline algorithm / abnormal activity recognition algorithm / GPS / machine learning / two-phase abnormality detection algorithm / efficient algorithm / activity recognition algorithms / baseline algorithms / ensemble learning algorithm / 4.2 Algorithm / data mining / rst MCMC algorithm / online inference algorithms / ai plan recognition technology / probabilistic plan recognition algorithm / /

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