Simultaneous tracking & activity recognition (star) using many anonymous
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[1] Donald Reid. The application of multiple target tracking theory to ocean surveillance , 1979, 1979 18th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.
[2] Y. Bar-Shalom. Tracking and data association , 1988 .
[3] G. C. Wei,et al. A Monte Carlo Implementation of the EM Algorithm and the Poor Man's Data Augmentation Algorithms , 1990 .
[4] Mitchell P. Marcus,et al. Parsing a Natural Language Using Mutual Information Statistics , 1990, AAAI.
[5] L. Burgio,et al. Studying disruptive vocalization and contextual factors in the nursing home using computer-assisted real-time observation. , 1994, Journal of gerontology.
[6] Thad Starner,et al. Visual Recognition of American Sign Language Using Hidden Markov Models. , 1995 .
[7] Douglas C. Montgomery,et al. Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .
[8] Katia P. Sycara,et al. Distributed Intelligent Agents , 1996, IEEE Expert.
[9] Bradley J. Rhodes,et al. The wearable remembrance agent: A system for augmented memory , 1997, Digest of Papers. First International Symposium on Wearable Computers.
[10] K. Buckwalter,et al. Measuring problem behaviors in dementia: developing a methodological agenda. , 1997, ANS. Advances in nursing science.
[11] M. Lawton,et al. Methodological aspects of the study of streams of behavior in elders with dementing illness. , 1997, Alzheimer disease and associated disorders.
[12] Stuart J. Russell,et al. Object identification in a Bayesian context , 1997, IJCAI 1997.
[13] J. Mcneil. Disabilities affect one-fifth of all Americans: Proportion could increase in coming decades , 1997 .
[14] Ingrid Zukerman,et al. Towards a Bayesian Model for Keyhole Plan Recognition in Large Domains , 1997 .
[15] Andrew McCallum,et al. A comparison of event models for naive bayes text classification , 1998, AAAI 1998.
[16] Jeff A. Bilmes,et al. A gentle tutorial of the em algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models , 1998 .
[17] J. Langford,et al. Monte Carlo Hidden Markov Models , 1998 .
[18] Alex Pentland,et al. Auditory Context Awareness via Wearable Computing , 1998 .
[19] Michael C. Mozer,et al. The Neural Network House: An Environment that Adapts to its Inhabitants , 1998 .
[20] Shlomo Argamon,et al. Committee-Based Sample Selection for Probabilistic Classifiers , 1999, J. Artif. Intell. Res..
[21] Aaron F. Bobick,et al. A Framework for Recognizing Multi-Agent Action from Visual Evidence , 1999, AAAI/IAAI.
[22] Takeo Kanade,et al. Advances in Cooperative Multi-Sensor Video Surveillance , 1999 .
[23] Yaacov Ritov,et al. Tracking Many Objects with Many Sensors , 1999, IJCAI.
[24] Irfan A. Essa,et al. Exploiting human actions and object context for recognition tasks , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[25] Arnaud Doucet,et al. Markov chain Monte Carlo data association for target tracking , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).
[26] Barry Brumitt,et al. EasyLiving: Technologies for Intelligent Environments , 2000, HUC.
[27] Chad Burkey. Environmental interfaces: HomeLab , 2000, CHI Extended Abstracts.
[28] Gregory D. Abowd,et al. Charting past, present, and future research in ubiquitous computing , 2000, TCHI.
[29] Gregory D. Abowd,et al. Living laboratories: the future computing environments group at the Georgia Institute of Technology , 2000, CHI Extended Abstracts.
[30] Patrick Pérez,et al. The (MR)MTPF: particle filters to track multiple targets using multiple receivers , 2001 .
[31] Wolfram Burgard,et al. Particle Filters for Mobile Robot Localization , 2001, Sequential Monte Carlo Methods in Practice.
[32] Michael J. Black,et al. Learning image statistics for Bayesian tracking , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[33] Nando de Freitas,et al. Sequential Monte Carlo in Practice , 2001 .
[34] George Casella,et al. Implementations of the Monte Carlo EM Algorithm , 2001 .
[35] Gaetano Borriello,et al. Location Systems for Ubiquitous Computing , 2001, Computer.
[36] Michael K. Pitt,et al. Auxiliary Variable Based Particle Filters , 2001, Sequential Monte Carlo Methods in Practice.
[37] Fredrik Gustafsson,et al. Monte Carlo data association for multiple target tracking , 2001 .
[38] L. Burgio,et al. Temporal patterns of disruptive vocalization in elderly nursing home residents , 2001, International journal of geriatric psychiatry.
[39] Andy Hopper,et al. Implementing a Sentient Computing System , 2001, Computer.
[40] Eric Horvitz,et al. Layered representations for human activity recognition , 2002, Proceedings. Fourth IEEE International Conference on Multimodal Interfaces.
[41] Martha E. Pollack,et al. Execution monitoring with quantitative temporal Bayesian networks , 2002 .
[42] Sakuko Otake,et al. Long-term remote behavioral monitoring of the elderly using sensors installed in domestic houses , 2002, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology.
[43] Neil J. Gordon,et al. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..
[44] Kenji Mase,et al. Activity and Location Recognition Using Wearable Sensors , 2002, IEEE Pervasive Comput..
[45] Wolfram Burgard,et al. Learning motion patterns of persons for mobile service robots , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).
[46] Paul R. Cohen,et al. An Unsupervised Algorithm for Segmenting Categorical Timeseries into Episodes , 2002, Pattern Detection and Discovery.
[47] Dieter Fox,et al. Bayesian Filtering for Location Estimation , 2003, IEEE Pervasive Comput..
[48] Frank Dellaert,et al. Efficient particle filter-based tracking of multiple interacting targets using an MRF-based motion model , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).
[49] T. Togawa,et al. The concept of the home health monitoring , 2003, Proceedings 5th International Workshop on Enterprise Networking and Computing in Healthcare Industry (HealthCom).
[50] Allison Woodruff,et al. The mad hatter's cocktail party: a social mobile audio space supporting multiple simultaneous conversations , 2003, CHI '03.
[51] Alex Pentland,et al. Sensing and modeling human networks using the sociometer , 2003, Seventh IEEE International Symposium on Wearable Computers, 2003. Proceedings..
[52] Shuichi Yoshino,et al. A new in-door location detection method adopting learning algorithms , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..
[53] C. Atkeson,et al. Toward the Automatic Assessment of Behavioral Distrubances of Dementia , 2003 .
[54] Telecommunications Board,et al. IT Roadmap to a Geospatial Future , 2003 .
[55] William C. Mann,et al. Enabling location-aware pervasive computing applications for the elderly , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..
[56] D. Fox,et al. Bayesian Techniques for Location Estimation , 2003 .
[57] Christopher G. Atkeson,et al. The Narrator : A Daily Activity Summarizer Using Simple Sensors in an Instrumented Environment , 2003 .
[58] Henry A. Kautz,et al. Inferring High-Level Behavior from Low-Level Sensors , 2003, UbiComp.
[59] Henry A. Kautz,et al. Guide: Towards Understanding Daily Life via Auto- Identification and Statistical Analysis , 2003 .
[60] Stanislav Kovacic,et al. Trajectory Based Assessment of Coordinated Human Activity , 2003, ICVS.
[61] Kent Larson,et al. Tools for Studying Behavior and Technology in Natural Settings , 2003, UbiComp.
[62] Christopher G. Atkeson,et al. Predicting human interruptibility with sensors: a Wizard of Oz feasibility study , 2003, CHI '03.
[63] Paul R. Cohen,et al. Bayesian Clustering by Dynamics Contents 1 Introduction 1 2 Clustering Markov Chains 2 , 2022 .
[64] Frank Dellaert,et al. EM, MCMC, and Chain Flipping for Structure from Motion with Unknown Correspondence , 2004, Machine Learning.
[65] Lars Erik Holmquist,et al. Supporting group collaboration with interpersonal awareness devices , 1999, Personal Technologies.
[66] Donald E. Brown,et al. Health-status monitoring through analysis of behavioral patterns , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.
[67] J. Movellan. Tutorial on Hidden Markov Models , 2006 .