A COMPARISON AND EVALUATION OF MOTION INDEXING ...

Basically, all of the relational features defined above assume the feature value zero
corresponds to a neutral, standing pose.
3.1.3 Threshold Selection
When the relational features are designed, it becomes very important to have
an appropriate threshold parameter θ for each feature function which is semantically
meaningful. The specific choice of a threshold has a strong influence on the semantics
of the resulting relational feature. If the threshold is increased, the feature functions
will not be able to detect subtle movements. The threshold selection is purely depen-
dent on the application in use. To make the relational features invariant under global
scaling, the threshold parameter θ is specified relative to the respective skeleton size.
Thresholds of most of the feature functions in the algorithm are expressed in terms
of humerus length, and some in terms of hip width or shoulder width. By doing this,
the threshold becomes independent of the skeleton size. Difference in the sizes of
skeletons due to different actors can be handled by this approach.
3.1.4 Formation of Document
A set of 19 geometric feature functions are selected to create a structure, doc-
ument. The description of these features is given in Table 3.1:
3.1.5 Adaptive Segmentation
A fixed combination of 19 geometric feature functions are applied to obtain the
document Γ for each motion sequence. The document is a matrix of zeros and ones for
all frames. Some of the consecutive frames in the motion sequence can yield the same
feature vectors which are known as runs. This can be mathematically explained as:
Given the fixed feature function F : ℜ 3J → {0, 1} f , then two poses P1, P2 ∈ ℜ 3J are
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