The Understanding of Meaningful Events in Gesture-Based Interaction - Intelligent Video Event Analysis and Understanding - page 6

false positives. This is important in unknown scenarios where color or motion-
based reasoning may fail cause of complex backgrounds to analyze (such as
crowded scenes with multiple motion sources or objects that present the same
color as the human skin);

Systems that employ general tracking algorithms usually require an initialization
stage during which the object to be tracked needs to be presented to the system.
A special location or a combination between location and posture are usually
employed in order to initialize such trackers;

￿

The segmentation process of a gesture is considerably facilitated if the start and
ending locations are known in advance. Segmenting gestures from continuous
movements is a difficult task hence knowing where and when a gesture started
and when it ended by simple location event triggers is definitely a plus on system
robustness.

￿

Location-based events are triggered whenever motion, color or other features are
identified in such predefined regions of interest. They may specify when the ges-
ture started, when it ended or whether it passed through some intermediate stage
towards completion. If the scenario is known and the location fixed and static (for
example when working at a desk with the video camera monitoring the tabletop as
Figure 3 illustrates), the regions may be simply defined during first-time installa-
tion and calibration of the system. For example, Vatavu and Pentiuc [50] use such
location-based events in order to detect and track hand postures only when hands
are positioned in predefined regions on the surface of the interactive coffee table
prototype. As the scenario is a static one (or unlikely to change much since installa-
tion), the calibration procedure represented by identifying and defining the regions
of interest is promising to produce robust results.
However, if the scenario is dynamic and likely to change over time (e.g. what
a mobile robot will see during its travel), the common solution is to use a robust
technique that would identify some aspect of the human body and then monitor

Fig. 3 Static scenario corresponding to a fixed camera installation for which regions of in-
terest were defined during system setup and calibration. Left: processing can be reduced to
limited regions only and even hand-wise delimitation is possible. Right: special regions such
as the keyboard (1) or printer (4) areas could trigger special events.