The use of pervasive sensing for behaviour profiling—a survey
L Atallah, GZ Yang - Pervasive and mobile computing, 2009 - Elsevier
With the maturity of sensing and pervasive computing techniques, extensive research is
being carried out in using different sensing techniques for understanding human behaviour …
being carried out in using different sensing techniques for understanding human behaviour …
Learning and detecting activities from movement trajectories using the hierarchical hidden Markov model
NT Nguyen, DQ Phung, S Venkatesh… - 2005 IEEE Computer …, 2005 - ieeexplore.ieee.org
Directly modeling the inherent hierarchy and shared structures of human behaviors, we
present an application of the hierarchical hidden Markov model (HHMM) for the problem of …
present an application of the hierarchical hidden Markov model (HHMM) for the problem of …
Development environments for autonomous mobile robots: A survey
J Kramer, M Scheutz - Autonomous Robots, 2007 - Springer
Abstract Robotic Development Environments (RDEs) have come to play an increasingly
important role in robotics research in general, and for the development of architectures for …
important role in robotics research in general, and for the development of architectures for …
Efficient duration and hierarchical modeling for human activity recognition
A challenge in building pervasive and smart spaces is to learn and recognize human
activities of daily living (ADLs). In this paper, we address this problem and argue that in …
activities of daily living (ADLs). In this paper, we address this problem and argue that in …
Growing hidden markov models: An incremental tool for learning and predicting human and vehicle motion
D Vasquez, T Fraichard… - The International Journal …, 2009 - journals.sagepub.com
Modeling and predicting human and vehicle motion is an active research domain. Owing to
the difficulty in modeling the various factors that determine motion (eg internal state …
the difficulty in modeling the various factors that determine motion (eg internal state …
Incremental learning of statistical motion patterns with growing hidden markov models
D Vasquez, T Fraichard… - IEEE Transactions on …, 2009 - ieeexplore.ieee.org
Modeling and predicting human and vehicle motion is an active research domain. Due to the
difficulty of modeling the various factors that determine motion (eg, internal state and …
difficulty of modeling the various factors that determine motion (eg, internal state and …
Using accelerometer, high sample rate GPS and magnetometer data to develop a cattle movement and behaviour model
The study described in this paper developed a model of animal movement, which explicitly
recognised each individual as the central unit of measure. The model was developed by …
recognised each individual as the central unit of measure. The model was developed by …
Robot introspection through learned hidden markov models
In this paper we describe a machine learning approach for acquiring a model of a robot
behaviour from raw sensor data. We are interested in automating the acquisition of …
behaviour from raw sensor data. We are interested in automating the acquisition of …
Approximation and randomization for quantitative information-flow analysis
B Köpf, A Rybalchenko - 2010 23rd IEEE Computer Security …, 2010 - ieeexplore.ieee.org
Quantitative information-flow analysis (QIF) is an emerging technique for establishing
information-theoretic confidentiality properties. Automation of QIF is an important step …
information-theoretic confidentiality properties. Automation of QIF is an important step …
Intentional motion on-line learning and prediction
Predicting motion of humans, animals and other objects which move according to internal
plans is a challenging problem. Most existing approaches operate in two stages:(a) learning …
plans is a challenging problem. Most existing approaches operate in two stages:(a) learning …