Research Projects

Visual Surveillance. Members: Massimo Piccardi, Hatice Gunes

Computer vision-based video surveillance aims to provide computer assistance to the human analysis of surveillance footage that could be used in real systems. It involves many different techniques of computer vision to analyse the shape motion and other appearance features of the surveillance footage. Object tracking is seen as one of the more useful aspects of this research with people tracking being a more complicated subset of the general tracking problem as humans are deformable objects that are also prone to self-occlusion. Human environments also tend to be less structured and more crowded than other environments increasing the difficulty of object and feature extraction. Surveillance systems of such environments are also likely to consist of many camera views that are disjointed, often significantly, making object motion cues unavailable for parts of the path. Such scenarios are common because of the cost of acquiring enough equipment to provide full coverage, especially with high enough resolution to measure accurate biometric information.

A video surveillance research project within the Computer Vision Research Group (CVRG) at UTS looks at building on this existing surveillance scenario to track individuals by matching appearance features between cameras. This is done using session-based biometrics where a surveillance session is defined as the segment of time from when an individual enters a building`s surveillance system, moves around inside the surveillance area and then exits. A typical surveillance session would be a portion of one day as people enter the workplace to conduct their business before leaving. Thus features such as clothing colour and clothed height would tend to remain constant throughout a single surveillance session, even if they might not be consistent over a longer period as people often change their clothes and shoes from day to day. Such features are not enough to necessarily identify a person as might be expected from fingerprints; however it can be used to distinguish between people. By analysing enough features the matches between individuals as they move about can obtained to a high degree of confidence. The current research is based upon fusing the information of height and colour features to provide a base framework for the use of track matching in generating disjoint camera matching.

Recent Grants CVRG has recently been awarded the following competitive research grants to support and extend their video surveillance activities:

UTS internal research grant (Research Excellence Grant scheme), 2003, $18,000
ARC Discovery Project DP0452657, 2004-2006, $168,000
AusIndustry Start Graduate, 2004-2005, $16,274
ARC Linkage Project LP0668325, 2006-2008, $354,000

Current Research Projects

	Ad-hoc Location-based Services for Mobile Multimedia. (D. Hoang, J. Chan)
	Cloud Computing and Distributed Systems. (A/Prof. Jinjun Chen, Prof. Doan Hoang, Lingfeng Chen (PhD student), Chang Liu (PhD student), Xuyun Zhang (PhD student), Gaofeng Zhang (PhD student))
	Compressive sensing of time series for human action recognition. (Oscar Perez Concha, Richard Yi Da Xu, Massimo Piccardi)
	Delayed-Multicast for video-on-demand. (D. Hoang, X. He, C. Nguyen)
	Distributed Systems and Service Discovery. (D. Hoang, B. Yousef)
	HMM-MIO: an enhanced hidden Markov model for action recognition. (Ehsan Zare Borzeshi, Oscar Perez Concha, Richard Yi Da Xu, Massimo Piccardi)
	Interactive Visualisation & Visual Analytics of Large Social Networks. (Mao Lin Huang)
	Large Scale Data Visualization. (Mao Lin Huang and Quang Vinh Nguyen)
	Network Congestion Control Modelling. (D. Hoang, M. Li)
	Optical Networking and Control Plane Intelligence. (D. Hoang)
	Peer-to-Peer Overlay Networks. (D. Hoang, H. Le, A. Simmonds)
	Personal Health Monitor. (Peter Leijdekkers and Valrie Gay)
	Programmable/Active Service Platform. (D. Hoang, B. Yousef)
	QoS Mechanisms over Wireless Internet. (D. Hoang, H. Zhou, P. Nhan)
	Scalable End-to-End Policy Routing and Traffic engineering over the Internet. (P. Nanda and A. Simmonds)
	Sign Text Detection from Outdoor Scene. (Xiangjian (Sean) He, Wenjing Jia)
	Spiral Architecture. (Xiangjian (Sean) He, Qiang Wu, Wenjing Jia)
	Vehicle Occupants Detection. (Xiangjian (Sean) He, Wenjing Jia)
	Visual Affective Computing. (Massimo Piccardi, Hatice Gunes)
	Visual Surveillance. (Massimo Piccardi, Hatice Gunes)

Past Research Projects

	Fair Intelligent Quality of Service Control and Path Discovery Mechanisms for Internet Scalable Architectures. (D. Hoang, U. Szewcow, M. Li)
	Fused Data Visualization. (Mao Lin Huang and Wu Quan)