a simulation framework for camera sensor networks research
We present our progress on the Virtual Vision paradigm, which prescribes visually and behaviorally realistic virtual environments, called "reality emulators", as a simulation tool to facilitate research on large-scale camera sensor networks. We have successfully exploited a prototype reality emulator---a virtual train station populated with numerous autonomous pedestrians---to rapidly develop novel solutions to challenging problems, such as multi-camera control and scheduling for persistent human surveillance by next-generation networks of smart cameras deployed in extensive public spaces.
virtual vision multi-camera control and scheduling persistent surveillance simulated camera sensor networks computer vision virtual reality