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REN Feng-lei, ZHOU Hai-bo, YANG Lu, HE Xin. Lane detection based on dual attention mechanism[J]. Chinese Optics. doi: 10.37188/CO.2022-0033
Citation: REN Feng-lei, ZHOU Hai-bo, YANG Lu, HE Xin. Lane detection based on dual attention mechanism[J]. Chinese Optics. doi: 10.37188/CO.2022-0033

Lane detection based on dual attention mechanism

doi: 10.37188/CO.2022-0033
Funds:  Supported by Key projects of Tianjin Natural Science Foundation (No. 17JCZDJC30400); Special Project for Research and Development in Key Areas of Guangdong Province (No. 2019B090922002)
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  • In order to improve the performance of lane detection algorithms under complex scenes like obstacles, we have proposed a multi-lane detection method based on dual attention mechanism in this paper. Firstly, we designed a lane segmentation network based on a spatial and channel attention mechanism. With this, we obtain a binary image which shows lane pixels and the background region. Then, we introduced HNet which can output a perspective transformation matrix and transform the image to a bird’s eye view. Next, we did curve fitting and transformed the result back to the original image. Finally, we defined the region between the two-lane lines near the middle of the image as the ego lane. Our algorithm achieves a 96.63% accuracy with real-time performance of 134 FPS on the Tusimple dataset. In addition, it obtains 77.32% of precision on the CULane dataset. The experiments show that our proposed lane detection algorithm can detect multi-lane lines under different scenarios including obstacles. Our proposed algorithm shows more excellent performance compared with the other traditional lane line detection algorithms.

     

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