Motion Detection for Nearby Vehicles

Author: Chia-Pei Chen(Department of Computer Science and Information Engineering,NTNU),Chiung-Yao Fang(Department of Information and Computer Education,NTNU),Sei-Wang Chen(Department of Computer Science and Information Engineering,NTNU)

Vol.&No.：Vol. 47, No. 2
Date：October 2002
Pages：1-26
DOI：10.6301/JNTNU.2002.47(2).01

Abstract：

We propose a system which can detect the motion patterns of nearby vehicles on an expressway. The system consists of three components: sensory, perceptual, and conceptual. The sensory component can extract the spatial and temporal information about the moving objects, including nearby vehicles. The perceptual component uses a STA (spatial-temporal attention) neural network to form "attention maps" which indicate the motion direction of nearby vehicles. We divide these attention maps into five overlapping windows in order to analysis more then one vehicle motions. We extract skewness features from each window. These features are fed into their corresponding CART (configurable adaptive resonance theory) neural network in conceptual component for classification. Using a modify fuzzy integral technique, individual decisions are made by each CART neural network, and then these decisions are collected to make the final decision about the motion class of the moving vehicle.

Keywords：Motion Detection,Vehicle Detection,Fuzzy integral

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