Real-time crowdedness measuring system for Taejon EXPO '93

Measuring the crowdedness of a public area can be very useful for preventing from the multitudinous situation in advance and for properly scheduling the frequency of services. We have developed a vision-based crowdedness measuring system for Taejon Expo '93. The system identifies human bodies by using the vision technique that detects moving objects through a series of differencing processes, and, in turn, estimates the distribution of human in wide regions. To ensure robustness on the real outdoor environment, the human detection algorithm exploits three key concepts: multiple features fusion approach, image sequence generation with varied time intervals, and high-level knowledge about the geometry of the scene. The entire venue is divided into several meaningful regions and each region is also divided into several scenes for the realtime analysis. Each scene is obtained from one of twenty-five CCD cameras which cover the critical ares of the venue. Crowdedness analysis algorithm calculates the crowdedness of each scene and combines the results into the region crowdedness. The system was fully functional during the entire period of Taejon EXPO '93.