Abstract
Detecting moving objects in a dynamic scene is a difficult task in computer vision. We propose a moving object detection algorithm for advanced driver assistance systems that uses only images from a monocular camera. To distinguish moving objects from standing objects when the camera is moving, we used an epipolar line constraint and an optical flow constraint. When evaluated using the KITTI scene flow 2015 dataset, the proposed algorithm detected moving objects in the image successfully even when the monocular camera was moving. The runtime of the proposed algorithm is < 1 s, so it is feasible for practical uses.
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Acknowledgement
This work was supported by the Human Resource Training Program for Regional Innovation and Creativity through the Ministry of Education and National Research Foundation of Korea.
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Ha, J., Jun, W., Jeong, H. (2016). Moving Object Detection Using SIFT Matching on Three Frames for Advanced Driver Assistance Systems. In: Chmielewski, L., Datta, A., Kozera, R., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2016. Lecture Notes in Computer Science(), vol 9972. Springer, Cham. https://doi.org/10.1007/978-3-319-46418-3_42
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