ECCV 2012 - LNCS 7572-7578 and 7583-7585

Subtraction-Based Forward Obstacle Detection Using Illumination Insensitive Feature for Driving-Support

Haruya Kyutoku¹, Daisuke Deguchi², Tomokazu Takahashi³, Yoshito Mekada⁴, Ichiro Ide¹, and Hiroshi Murase¹

¹Graduate School of Information Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi, 464-8601, Japan

²Information and Communications Headquarters, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi, 464-8601, Japan

³Faculty of Economics and Information, Gifu Shotoku Gakuen University, 1-38, Nakauzura, Gifu, Gifu, 500-8288, Japan

⁴School of Information Science and Technology, Chukyo University, 101, Tokodachi, Kaizu-cho, Toyota, Aichi, 470-0393, Japan

Abstract. This paper proposes a method for detecting general obstacles on a road by subtracting present and past in-vehicle camera images. The image-subtraction-based object detection approach can be applied to detect any kind of obstacles although the existing learning-based methods detect only specific obstacles. To detect general obstacles, the proposed method first computes a frame-by-frame correspondence between the present and the past in-vehicle camera image sequences, and then registrates road surfaces between the frames. Finally, obstacles are detected by applying image subtraction to the registrated road surface regions with an illumination insensitive feature for robust detection. Experiments were conducted by using several image sequences captured by an actual in-vehicle camera to confirm the effectiveness of the proposed method. The experimental results shows that the proposed method can detect general obstacles accurately at a distance enough to avoid them safely even in situations with different illuminations.

LNCS 7584, p. 515 ff.

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