Snapshot of Research
|EU FP7 Security Programme Project SUNNY (2014-2018) – Smart UNmanned aerial vehicle sensor Network for detection of border crossing and illegal entrY|
|EU FP7 Security Programme Project SmartPrevent (2014-2016) – Smart video-surveillance system to detect and prevent local crimes in urban areas|
|Cross-Domain Behaviour Understanding
Current behaviour understanding approaches suffer from highly contraint on the uniform of behaviour distribution, feature representation and etc between training and testing data. These approaches might fail when the testing data is changing all the time (e.g. UAV surveillance). We developed a cross-domain traffic scene understanding framework to interpret unseen events in target domain without training procedure by transferring knowledge learned from existing source domains.
|Sketch Recognition by Ensemble Matching of Structured Features
We present a method for the representation and matching of sketches by exploiting not only local features but also global structures of sketches, through a star graph based ensemble matching strategy. We further show that by encapsulating holistic structure matching and learned bag-of-features models into a single framework, notable recognition performance improvement over the state-of-the-art can be observed.
Attribute Learning for Understanding Unstructured Social Activity
The USAA dataset includes 8 different semantic class videos which are home videos of social occassions such e birthday party, graduation party,music performance, non-music performance, parade, wedding ceremony, wedding dance and wedding reception which feature activities of group of people.
Recently Completed Projects
|INSIGHT: Video Analysis and Selective Zooming using Semantic Models of Human Presence and Activity (2004-2007)INSIGHT is an EPSRC and MOD DSTL jointly funded three years project under the EPSRC Technologies for Crime Prevention and Detection Programme.
INSIGHT aims to advance the state-of-the-art in semantic content analysis of CCTV recordings for automatic semantic video tagging, search and pro-active sampling. Shaogang Gong, Tony Xiang, Melanie Aurnhammer, David Russell, Chris Jia Kui and Andrew Graves
|SAMURAI: Suspicious and Abnormal behaviour Monitoring Using a netwoRk of cAmeras for sItuation awareness enhancement
SAMURAI is a collaborative project funded under the European Commission Seventh Framework Programme Theme 10 (Security). The aim of SAMURAI is to develop and integrate an innovative intelligent surveillance system for monitoring people and vehicle activities at both inside and surrounding areas of a critical public infrastructure.
|BEWARE: Behaviour based Enhancement of Wide-Area Situational Awareness in a Distributed Network of CCTV Cameras
BEWARE is a project funded by EPSRC and MOD to develop models for video-based people tagging (consistent labelling) and behaviour monitoring across a distributed network of CCTV cameras for the enhancement of global situational awareness in a wide area.