EFFECTIVE PEDESTRIAN DETECTION IN LOW-CONTRAST IMAGES(International Workshop on Advanced Image Technology 2006)

概要

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This paper proposes an accurate pedestrian detection method in low-contrast images by using Support Vector Machine (SVM). The proposed pedestrian detection is realized by the following two systems : (1) Moving object extraction system In the low contrast case, traditional methods cannot extract the moving objects successfully. Therefore, in order to accurately extract the objects, the proposed method adopts hierarchical procedures depending on the intensity levels of the low-contrast images. (2) Pedestrian decision system From the objects extracted by (1), two features, which are the ratio between the width and the height and the moving speed, are computed. Pedestrian decision is executed by inputting these features to the SVM. By using these two systems, the features can be accurately extracted, and the SVM using these features can successfully judge whether the moving object is a pedestrian or not. Consequently, the proposed method can accurately detect the pedestrian in low-contrast images. Some experimental results are shown to verify the effectiveness of the proposed method.
社団法人電子情報通信学会の論文
2006-01-02