Abstract
Intelligentization of car navigation is an inevitable trend. Visual navigation has the advantages of high precision in short distances and low cost. This paper proposes a fuzzy control reversing system based on visual information. We obtain the trajectory of the rear camera by constructing reversing model of the car. YOLO (You Only Look Once) is used to detect pedestrians and cars appearing in the camera field of view and segment the detected images during the reversing process. The dynamic feature points are removed effectively by the proposed environmental statistical information analysis method. Using visual information to construct constraints to improve the traditional fuzzy control reversing system can provide drivers with accurate driving assistance information and effectively reduce the probability of accidents such as collisions. The experimental results show that the proposed method is effective and feasible.
This work is supported by the open fund of Shaanxi Key Laboratory of Integrated and Intelligent Navigation SKLIIN-20180102 and SKLIIN-20180107. This is a student work.
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Liu, S., Fan, Y., Tang, Y., Jing, X., Yao, J., Han, H. (2019). Fuzzy Control Reversing System Based on Visual Information. In: Lin, Z., et al. Pattern Recognition and Computer Vision. PRCV 2019. Lecture Notes in Computer Science(), vol 11859. Springer, Cham. https://doi.org/10.1007/978-3-030-31726-3_21
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