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tal results from the analysis of facial expressions and hand gestures in video
sequences. In the case of facial expressions, the motion of tracked feature points
is translated to MPEG-4 FAPs, which describe their observed motion in a high-
level manner. Regarding hand gestures, hand segments are located in a video
sequence via color segmentation and motion estimation algorithms. The position
of these segments is tracked to provide the hand's position over time and fed into
a HMM architecture to provide affective gesture estimation.
In most cases, a single expression or gesture cannot help the system deduce a
positive decision about the users' observed emotion. As a result, a fuzzy
architecture is employed that uses the symbolic representation of the tracked
features as input. This concept is described in the section “Multimodal affective
analysis.” The decision of the fuzzy system is based on rules obtained from the
extracted features of actual video sequences showing emotional human dis-
course, as well as feature-based description of common knowledge of what
everyday expressions and gestures mean. Results of the multimodal affective
analysis system are provided here, while conclusions and future work concepts
are included in the final section “Conclusions - Future work.”
Affective Analysis in MMI
Representation of Emotion
The obvious goal for emotion analysis applications is to assign category labels
that identify emotional states. However, labels as such are very poor descrip-
tions, especially since humans use a daunting number of labels to describe
emotion. Therefore, we need to incorporate a more transparent, as well as
continuous, representation that more closely matches our conception of what
emotions are or, at least, how they are expressed and perceived.
Activation-emotion space (Whissel, 1989) is a representation that is both simple
and capable of capturing a wide range of significant issues in emotion (Cowie et
al., 2001). Perceived full-blown emotions are not evenly distributed in this space;
instead, they tend to form a roughly circular pattern. From that and related
evidence, Plutchik (1980) shows that there is a circular structure inherent in
emotionality. In this framework, emotional strength can be measured as the
distance from the origin to a given point in activation-evaluation space. The
concept of a full-blown emotion can then be translated roughly as a state where
emotional strength has passed a certain limit. A related extension is to think of
primary or basic emotions as cardinal points on the periphery of an emotion
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