Abstract
Vision-Based solution of safe navigation for commercial vehicles with fish-eye camera is presented in this paper. This work aims to develop a system which is able to detect persons or objects around commercial vehicles for preventing any accidents. This is achieved by integrating classifier-based window searching algorithm and ego-motion-based algorithm into the system. The classifier is trained using cascaded support vector machine and ego-motion is estimated only based on captured images from camera. Test results show that designed system provides high detection rate when it is applied in commercial vehicle.
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Acknowledgments
This research has been supported by European Union Seventh Framework Program (FP7/2007-2013) under grant agreement number 285417 and German Federal Ministry of Education and Research (BMBF).
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Piao, S., Berns, K. (2016). Vision-Based Person Detection for Safe Navigation of Commercial Vehicle. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_38
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DOI: https://doi.org/10.1007/978-3-319-08338-4_38
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