Abstract:The driving environment at night is more complex than that during the day, so the perception of the driving environment at night by the assistant driving system is very important. For pedestrian recognition, the traditional pedestrian trajectory and intention estimation algorithm is not suitable at night. To estimate pedestrian intention and trajectory at night, a method was proposed for estimating pedestrian intention and trajectory in short distance under low brightness environment. The new image enhancement algorithm was used to improve the face recognition rate. For the enhanced image, the matching algorithm was proposed based on YOLOv3 and Openpose. The Kalman filter was used to correct the YOLOv3 recognition error, and a pedestrian face orientation estimation algorithm was proposed based on the matching results to obtain a new method for estimating pedestrian intention. The results show that the proposed pedestrian trajectory and intention estimation method is suitable for low luminance environment after image enhancement.
汪威, 罗石, 耿国庆, 刘军. 基于行人关键点的低亮度行人轨迹和意图估计[J]. 江苏大学学报(自然科学版), 2022, 43(4): 400-406.
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