This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …

Much research in artificial intelligence is concerned with the development of autonomous
agents that can interact effectively with other agents. An important aspect of such agents is …

Humans are adept at inferring the mental states underlying other agents' actions, such as
goals, beliefs, desires, emotions and other thoughts. We propose a computational …

Modelling sequential data is important in many areas of science and engineering. Hidden
Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they …

Predicting human behavior from a small amount of training examples is a challenging
machine learning problem. In this thesis, we introduce the principle of maximum causal …

Pervasive systems must offer an open, extensible, and evolving portfolio of services which
integrate sensor data from a diverse range of sources. The core challenge is to provide …

Over the past few years, several methods for segmenting a scene containing multiple rigidly
moving objects have been proposed. However, most existing methods have been tested on …

This paper introduces a hierarchical Markov model that can learn and infer a user's daily
movements through an urban community. The model uses multiple levels of abstraction in …

Plan recognition, activity recognition, and intent recognition together combine and unify
techniques from user modeling, machine vision, intelligent user interfaces, human/computer …

As robots become more and more capable and autonomous, there is an increasing need for
humans to understand what the robots do and think. In this paper, we investigate what such …