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2012 | OriginalPaper | Chapter

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

Authors : Haruya Kyutoku, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

Published in: Computer Vision – ECCV 2012. Workshops and Demonstrations

Publisher: Springer Berlin Heidelberg

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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.

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Metadata
Title
Subtraction-Based Forward Obstacle Detection Using Illumination Insensitive Feature for Driving-Support
Authors
Haruya Kyutoku
Daisuke Deguchi
Tomokazu Takahashi
Yoshito Mekada
Ichiro Ide
Hiroshi Murase
Copyright Year
2012
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-33868-7_51

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