Demo: A distributed virtual vision simulator

Abstract

Realistic virtual worlds can serve as laboratories for carrying out camera networks research. This unorthodox “Virtual Vision” paradigm advocates developing visually and behaviorally realistic 3D environments to serve the needs of computer vision. Our work on high-level coordination and control in camera networks is a testament to the suitability of virtual vision paradigm for camera networks research. The prerequisite for carrying out virtual vision research is a virtual vision simulator capable of generating synthetic imagery from simulated real-life scenes. We present a distributed, customizable virtual vision simulator capable of simulating pedestrian traffic in a variety of 3D environments. Virtual cameras deployed in this synthetic environment generate synthetic imagery — boasting realistic lighting effects, shadows, etc. — using the state-of-the-art computer graphics techniques. The synthetic imagery is fed into a “real-world” vision pipeline that performs visual analysis — e.g., blob detection and tracking, facial detection, etc. — and returns the results of this analysis to our simulated cameras for subsequent higher level processing. It is important to bear in mind that our vision pipeline is designed to handle real world imagery without any modifications. Consequently, it closely mimics the performance of a vision pipeline that one might deploy on physical cameras. Our virtual vision simulator is realized as a collection of modules that communicate with each other over the network. Consequently, we can deploy our simulator over a network of computers, allowing us to simulate much larger networks and much more complex scenes then is otherwise possible.