Visible to the public Intruder detection by extracting semantic content from surveillance videos

TitleIntruder detection by extracting semantic content from surveillance videos
Publication TypeConference Paper
Year of Publication2014
AuthorsHarish, P., Subhashini, R., Priya, K.
Conference NameGreen Computing Communication and Electrical Engineering (ICGCCEE), 2014 International Conference on
Date PublishedMarch
KeywordsCameras, feature extraction, features extraction, human activity recognition, intruder detection, object detection, object tracking, Ontologies, ontologies (artificial intelligence), Ontology, SCE, Semantic content, semantic content extraction, Semantics, Spatial and Temporal Relations, surveillance cameras, surveillance videos, video surveillance, Videos

Many surveillance cameras are using everywhere, the videos or images captured by these cameras are still dumped but they are not processed. Many methods are proposed for tracking and detecting the objects in the videos but we need the meaningful content called semantic content from these videos. Detecting Human activity recognition is quite complex. The proposed method called Semantic Content Extraction (SCE) from videos is used to identify the objects and the events present in the video. This model provides useful methodology for intruder detecting systems which provides the behavior and the activities performed by the intruder. Construction of ontology enhances the spatial and temporal relations between the objects or features extracted. Thus proposed system provides a best way for detecting the intruders, thieves and malpractices happening around us.

Citation Key6922469