アフィン変換を用いた特徴平面の移動に基づく車両前面検出

概要

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This paper proposes a novel vehicle detection method. It uses an affine transform to determine the planar of features visible on the vehicle front surface. The feature points are detected on the image obtained from an embedded camera. In general, it is said that the feature points can perform stable vehicle detection since they are robust to weather and illumination changes. However, the feature points are also detected from artifacts which appear in the background image. For removing unnecessary feature points, we consider the vehicle front surface as planar and assume it follows an affine transform. We find that this affine transform assumption is valid, and the optical flow of the plane is used to determine whether it belongs to the background or to a following vehicle. Namely, our system can differentiate the front face of following vehicle and the background. Our experiments confirm that our system can locate and track the rear and side vehicles accurately and robustly.