The prevailing practice of design for mass customization manifests itself through a configure-
to-order paradigm, which means to satisfy explicit customer needs (CNs) and built upon …

Recent advances in small inexpensive sensors, low-power processing, and activity
modeling have enabled applications that use on-body sensing and machine learning to infer …

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

Recent work on plan recognition as planning has shown great promise in the use of a
domain theory and general planning algorithms for the plan recognition problem. In this …

Plan recognition is the problem of inferring the goals and plans of an agent after observing
its behavior. Recently, it has been shown that this problem can be solved efficiently, without …

In this work we aim to narrow the gap between plan recognition and planning by exploiting
the power and generality of recent planning algorithms for recognizing the set G∗ of goals G …

We address the problem of visual event recognition in surveillance where noise and missing
observations are serious problems. Common sense domain knowledge is exploited to …

Plan recognition is the problem of inferring the goals and plans of an agent from partial
observations of her behavior. Recently, it has been shown that the problem can be …

Recognizing human activities from sensor readings has recently attracted much research
interest in pervasive computing due to its potential in many applications, such as assistive …

Systems that automatically recognize human activities offer the potential of timely, task-
relevant information and support. For example, prompting systems can help keep people …