MSE Research Project Database

Adaptive learning visual sensor networks for crowd modelling


Project Leader: Jayavardhana Gubbi Lakshminarasimha
Staff: Marimuthu Palaniswami, Slaven Marusic
Student: Aravinda Rao
Collaborators: Ba-Ngu Vo (University of Western Australia), Paul Stanley (ARUP), Andrew Maher (ARUP), Trevor Dohnt (Melbourne Cricket Club), Subhash Challa (SenSen Pty Ltd)
Sponsors: ARC Linkage Grant, ARUP, Melbourne Cricket Club, SenSen Networks Pty Ltd
Primary Contact: Jayavardhana Gubbi (jgl@unimelb.edu.au)
Keywords: artificial intelligence; machine learning; sensor networks; signals and systems
Disciplines: Electrical & Electronic Engineering
Domains: Networks and data in society
Research Centre: ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)

The prevalence of camera networks for surveillance, together with the decreasing cost of infrastructure, has produced a significant demand for robust monitoring systems. Current systems offer limited functionality, particularly in their reliance on centralised processing of gathered information. This project addresses end-to-end system challenges of wireless visual sensor networks. Integrating developments across the spatial, spatio-temporal and decision domains, the project will incorporate distributed sensor network technology with intelligent fusion of information, to deliver unique long-term behaviour analysis capabilities for efficient planning in highly crowded environments.