TY  - JOUR
AU  - Carles Fernandez
AU  - Pau Baiget
AU  - Xavier Roca
AU  - Jordi Gonzalez
PY  - 2011//
TI  - Determining the Best Suited Semantic Events for Cognitive Surveillance
T2  - EXSY
JO  - Expert Systems with Applications
SP  - 4068–4079
VL  - 38
IS  - 4
PB  - Elsevier
KW  - Cognitive surveillance
KW  - Event modeling
KW  - Content-based video retrieval
KW  - Ontologies
KW  - Advanced user interfaces
N2  - State-of-the-art systems on cognitive surveillance identify and describe complex events in selected domains, thus providing end-users with tools to easily access the contents of massive video footage. Nevertheless, as the complexity of events increases in semantics and the types of indoor/outdoor scenarios diversify, it becomes difficult to assess which events describe better the scene, and how to model them at a pixel level to fulfill natural language requests. We present an ontology-based methodology that guides the identification, step-by-step modeling, and generalization of the most relevant events to a specific domain. Our approach considers three steps: (1) end-users provide textual evidence from surveilled video sequences; (2) transcriptions are analyzed top-down to build the knowledge bases for event description; and (3) the obtained models are used to generalize event detection to different image sequences from the surveillance domain. This framework produces user-oriented knowledge that improves on existing advanced interfaces for video indexing and retrieval, by determining the best suited events for video understanding according to end-users. We have conducted experiments with outdoor and indoor scenes showing thefts, chases, and vandalism, demonstrating the feasibility and generalization of this proposal.
L1  - http://refbase.cvc.uab.es/files/FBR2011a.pdf
UR  - http://dx.doi.org/10.1016/j.eswa.2010.09.070
N1  - ISE
ID  - Carles Fernandez2011
ER  -