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72 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 1, NO. 2, JUNE 2000 A Vehicle Occupant Counting System Based on Near-Infrared Phenomenology and Fuzzy Neural Classification Ioannis Pavlidis , Senior Member, IEEE , Vassilios Morellas , Member, IEEE , and Nikolaos Papanikolopoulos , Member, IEEE Abstract— We undertook a study to determine if the automatic detection and counting of vehicle occupants is feasible. An auto- mated vehicle occupant counting system would greatly facilitate the operation of freeway lanes reserved for buses, car-pools, and emergency vehicles (HOV lanes). In the present paper, we report our findings regarding the appropriate sensor phenomenology and arrangement for the task. We propose a novel system based on fu- sion of near-infrared imaging signals and we demonstrate its ade- quacy with theoretical and experimental arguments. We also pro- pose a fuzzy neural network classifier to operate upon the fused near-infrared imagery and perform the occupant detection and counting function. We demonstrate experimentally that the com- bination of fused near-infrared phenomenology and fuzzy neural classification produces a robust solution to the problem of auto- matic vehicle occupant counting. We substantiate our argument by providing comparative experimental results for vehicle occupant counters based on visible, single near-infrared, and fused near-in- frared bands. Interestingly, our proposed solution can find a more general applicability as the basis for a reliable face detector both indoors and outdoors. Index Terms— Fuzzy neural network, near-infrared fusion, ve- hicle occupant detection. I. INTRODUCTION T HERE are compelling reasons for the existence of an auto- matic vehicle occupant counting system in the HOV lane. In particular, such a system will be useful in the following re- spects. 1) It will facilitate the gathering of statistical data for road construction planning. The gathering of usage statistics in the HOV lane is mandated by the U.S. Federal Highway Administration. Currently, the gathering of data is per- formed manually. This is obviously laborious, inefficient, and prone to error. 2) It will facilitate law enforcement in the HOV lane. Cur- rently, HOV lane enforcement requires substantial com- mitments of State Highway Patrol personnel and equip- ment. HOV lane enforcement has other costs as well. Manuscript received March 6, 2000; revised August 29, 2000. This work was supported by the Minnesota Department of Transportation under Contract Q5216211101.The Guest Editor for this paper was Dr. Katsushi Ikeuchi. I. Pavlidis and V. Morellas are with the Honeywell Technology Center, Min- neapolis, MN 55418 USA (e-mail: ioannis.pavlidis@honeywell.com; vassilios. morellas@honeywell.com).
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