Applications of Factorization Theorem and Ontologies for Activity ModelingRecognition and Anomaly Detection
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In this thesis two approaches for activity modeling and suspicious activity detection are
examined. First is application of factorization theorem extension for deformable models in two
dierent contexts. First is human activity detection from joint position information, and second
is suspicious activity detection for tarmac security. It is shown that the first basis vector from
factorization theorem is good enough to dierentiate activities for human data and to distinguish
suspicious activities for tarmac security data.
Second approach dierentiates individual components of those activities using semantic methodol-
ogy. Although currently mainly used for improving search and information retrieval, we show that
ontologies are applicable to video surveillance. We evaluate the domain ontologies from Challenge
Project on Video Event Taxonomy sponsored by ARDA from the perspective of general ontology
design principles. We also focused on the eect of the domain on the granularity of the ontology
for suspicious activity detection.