Finding and Indexing of Eccentric Events in Video Emanates
Year: 2010
Type: article
Abstract: — We propose a methodology that first extracts features of video emanates and detects eccentric events in a crowded environment. Afterwards eccentric events are indexed for retrieval. The motivation of the framework is the discrimination of features which are independent from the application domains. Low-level as well as mid-level features are generic and independent of the type of abnormality. High-level features are dependent and used to detect eccentric events, whereas both mid-level and high-level features are run through the indexing scheme for retrieval. To demonstrate the interest of the methodology, we primarily present the obtained results on collapsing events in real videos amassed by single camera installed an airport escalator exits to monitor the circumstances of those regions.
Source: Journal of Multimedia
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: European Commission
OpenAlex ID: W2018383379