Realistic 3D Simulation of Multiple Human recognition over Perception Sensor Network

Abstract

In this paper, we introduce a simulation approach for emulating a real-world human recognition system called a Perception Sensor Network (PSN). The proposed PSN system has fusion components for automatic localization and facial recognition that uses multiple Kinect sensors and pan-tilt-zoom (PTZ) cameras. We verified that the generic vision schemes utilized in human detection and facial recognition algorithms were interoperable in a scenario that consisted of virtual avatar humans. In experiments, we tested a perception scenario in which multiple humans in a 3D simulation space are automatically recognized in both location and identification with real-world system parameters.