Simultaneous Tracking and Activity Recognition (STAR) Using Many Anonymous, Binary Sensors

By Daniel H. Wilson, Christopher G. Atkeson. International Conference on Pervasive Computing, 2005

360 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/365a342532c342bf52341753dcfcdfdbcdb04fff

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In Artificial Intelligence

In Computer Vision and Pattern Recognition

In Electrical and Electronic Engineering

Citations in the corpus

Using a Live-In Laboratory for Ubiquitous Computing Research (2006, background): “Distributed sensors may improve redundancy as well, higher-level reasoning about activity structure to be easily encoded in useful For example, promising results have recently been obtained for recognizing activities in the using RFID gloves and contact switches superseding the capabilities of most ”
Recognizing daily activities with RFID-based sensors (2009, background): “Most common [21, 27, 1] are battery-powered matchbox-sized wireless accelerometers costing tens of dollars each.”
At the Flick of a Switch: Detecting and Classifying Unique Electrical Events on the Residential Power Line (Nominated for the Best Paper Award) (2007, background): “Another class of approaches explores the use of a large collection of simple, lowcost sensors, such as motion detectors, pressure mats, break beam sensors, and contact switches, to determine activity and movement [15, 16, 18].”
Accurate activity recognition in a home setting (2008, methodology): “tings, dynamic Bayesian networks were used to recognize the activities of multiple people in a house [20].”
A survey of computational location privacy (2009, neutral): “Wilson and Atkeson [64] placed simple presence”
A Long-Term Evaluation of Sensing Modalities for Activity Recognition (2007, background): “In particular, we focus on work using object usage (motion) detectors placed on large objects and furniture [1], body-worn accelerometers [5,4], magnetic reed switches [6,2], water/power system monitors [10] and wrist-worn RFID readers [8].”
Sensor-Based Activity Recognition (2012, background): “Wilson and Atkeson [82] use four kinds of anonymous and binary sensors, motion detectors, break-beam sensors, pressure mats, and contact switches for simultaneous tracking and”
A Survey on Ambient-Assisted Living Tools for Older Adults (2013, background): “Most graphical models are able to deal with the sequential nature of data, including Markov chains [72], Dynamic Bayesian Network (DBN) [73], [74], [75], Hidden Markov Model (HMM) [71], and Conditional Random Fields”
A Survey on Ambient Intelligence in Health Care (2013, neutral): “Environment sensors such as infrared motion detectors, magnetic door sensors, break-beam sensors, and pressure mats [47], [48] have been used to gather information about more complex activities such as cooking, sleeping, and eating.”