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Seminars will be held in the Lecture Theatre 1 - William Gates Building, Computer Laboratory at 4.15pm
for the research groups' seminars:

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Semantic Video Content Analysis for Security

Shaogang Gong*

Department of Computer Science,
Queen Mary University of London

There is a huge demand for fully automated semantic video content analysis due to massive increase of video media in the last decade. However, there is also a lack of effective analytical tools to extract automatically the most relevant information in context and in good time, especially when dealing with CCTV video data of public space. Significantly, human attention span usually lasts no more than 15-20 minutes resulting in highly inconsistent and error-prone manual based content labelling and extraction of CCTV video. Furthermore, the lack of any structured script or embedded meta-data in security and surveillance video, as is present in most commercial and entertainment video, makes the task of automated semantic content analysis of such video data extremely difficult.

In this talk, I will present recent results on activity event and behaviour based video content analysis of security and surveillance video. I will highlight that some of the fundamental problems in security video content analysis are more than merely object tracking and trajectory matching. I will address the problem of modelling and recognising complex activities involving simultaneous movement of multiple overlapped objects. Dynamic probabilistic graph models are exploited for modelling the temporal relationships among a set of different object temporal events and are used to profile and index salient event and behaviour patterns captured in CCTV video, and for the detection of atypical and abnormal behaviours. I will also briefly discuss the problem of extracting and synthesising high-resolution image patches of saliency in low-resolution CCTV content under motion blur, especially in the context of face recognition in low-resolution CCTV video.

Shaogang Gong is Professor of Visual Computation at Queen Mary, University of London, elected a Fellow of the Institution of Electrical Engineers, a member of the UK Computing Research Committee, and Head of Queen Mary Computer Vision Research Group he founded in 1993. He received his DPhil in computer vision from Oxford in 1989 with a thesis on the computation of optic flow using second-order geometric analysis. He is a recipient of a Queen's Research Scientist Award in 1987, a Royal Society Research Fellow in 1987 & 1988, and a GEC-Oxford fellow in 1989. He twice won the Best Science Prize of the British Machine Vision Conferences (1999 and 2001) and once won the Best Paper Award (2001) of the IEEE International Workshops on Recognition, Analysis and Tracking of Faces and Gestures. He is the principal author of a book on Dynamic Vision: From Images to Face Recognition (Imperial College Press, 2000). His work focuses on visual motion and video analysis with applications to the detection, tracking and recognition of vehicles and human objects, activity profiling, behaviour recognition and abnormality detection in CCTV & live video. A current significant focus is in security for crime prevention and detection funded by the MOD, EPSRC, DTI and industry.

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