1 INTRODUCTION
HUMAN activity recognition has become an important
application area for pattern recognition. Research in
computer vision has traditionally been at the forefront of
this work [1], [2]. The growing use of ambient and bodyworn
sensors has paved the way for other sensing
modalities, particularly in the domain of ubiquitous
computing. Important advances in activity recognition were
achieved using modalities such as body movement and
posture [3], sound [4], or interactions between people [5].
There are, however, limitations to current sensor configurations.
Accelerometers or gyroscopes, for example, are
limited to sensing physical activity; they cannot easily be used
for detecting predominantly visual tasks, such as reading,
browsing the Web, or watching a video. Common ambient
sensors, such as reed switches or light sensors, are limited in
that they only detect basic activity events, e.g., entering or
leaving a room or switching an appliance on or off. Further to
these limitations, activity sensing using subtle cues, such as
user attention or intention, remains largely unexplored.