|
|
Pedestrian trajectory and intention estimation under low brightness based on human key points |
School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China |
|
|
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.
|
|
|
|
|
[1] |
袁朝春,宋金行,何友国,等.基于行人轨迹预测的无人驾驶汽车主动避撞算法[J].江苏大学学报(自然科学版),2021,42(1):1-8.
|
|
YUAN C C, SONG J H, HE Y G, et al. Active collision avoidance algorithm of autonomous vehicle based on pedestrian trajectory prediction[J]. Journal of Jiangsu University(Natural Science Edition),2021,42(1):1-8. (in Chinese)
|
[2] |
SULISTIYO M D, KAWANISHI Y, DEGUCHI D, et al. ColAttnet: in reducing the ambiguity of pedestrian orientations on attributeaware semantic segmentation task[J]. IEEJ Transactions on Electrical and Electronic Engineering,2021,16(2):295-306.
|
[3] |
CAO D, FU Y B. Using graph convolutional networks skeletonbased pedestrian intention estimation models for trajectory prediction[J].Journal of Physics:Conference Series,doi:10.1088/1742-6596/1621/1/012047.
|
[4] |
冯欣,李永波,杨武.一种利用目标结构关系增强的行人重识别方法[J/OL].重庆理工大学学报(自然科学). http:∥kns.cnki.net/kcms/detail/50.1205.t.20220424.1455.002.html.
|
|
FENG X, LI Y B, YANG W. A structural relationship enhanced person reidentification method\[J/OL\].Journal of Chongqing University of Technology (Natural Science). http:∥kns.cnki.net/kcms/detail/50.1205.t.20220424.1455.002.html. (in Chinese)
|
[5] |
JOBSON D J, RAHMAN Z, WOODELL G A. A multiscale retinex for bridging the gap between color images and the human observation of scenes[J]. IEEE Transactions on Image Processing,1997,6(7):965-976.
|
[6] |
刘富,刘璐,侯涛,等.基于优化MSR的夜间道路图像增强方法[J].吉林大学学报(工学版),2021,51(1):323-330.
|
|
LIU F, LIU L, HOU T, et al. Night road image enhancement method based on optimized MSR[J]. Journal of Jilin University (Engineering and Technology Edition), 2021,51(1):323-330. (in Chinese)
|
[7] |
LIN H N, SHI Z W. Multiscale retinex improvement for nighttime image enhancement[J].Optik,2014,125(24):7143-7148.
|
[8] |
MA T T, YE W H, LENG S, et al. Solid waste surface feature enhancement method based on gamma correction and wavelet transform[J].Signal, Image and Video Processing,2021,15(7):1627-1634.
|
[9] |
FENG L G, LIN L. Image denoising methods based on wavelet transform and threshold functions[J]. Journal of Multimimedia Processing Technologies, 2017, 8(1): 1-10.
|
[10] |
朱铮涛,萧达安.基于非线性调整的伽马校正图像增强算法[J].计算机工程与设计,2018,39(9):2822-2826,2866.
|
|
ZHU Z T, XIAO D A. Gammacorrected image enhancement algorithm based on nonlinear adjustment[J].Computer Engineering and Design, 2018,39(9):2822-2826,2866. (in Chinese)
|
|
|
|