Citation: | LI Xun, LIU Yao, LI Peng-fei, ZHANG Lei, ZHAO Zheng-fan. Vehicle multi-target detection method based on YOLO v2 algorithm under darknet framework[J]. Journal of Traffic and Transportation Engineering, 2018, 18(6): 142-158. doi: 10.19818/j.cnki.1671-1637.2018.06.015 |
[1] |
OTTLIK A, NAGEL H H. Initialization of model-based vehicle-tracking in video sequences[J]. International Journal of Computer Vision, 2008, 80 (2): 211-225. doi: 10.1007/s11263-007-0112-6
|
[2] |
FLEYEH H, DAVAMI E. Eigen-based traffic sign recognition[J]. IET Intelligent Transport Systems, 2011, 5 (3): 190-196. doi: 10.1049/iet-its.2010.0159
|
[3] |
高云峰, 徐立鸿, 胡华, 等. 交叉口定周期信号控制多目标优化方法[J]. 中国公路学报, 2011, 24 (5): 82-88. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL201105014.htm
GAO Yun-feng, XU Li-hong, HU Hua, et al. Multiobjective optimization method for fixed-time signal control at intersection[J]. China Journal of Highway and Transport, 2011, 24 (5): 82-88. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL201105014.htm
|
[4] |
CHOIM K, PARK J, LEE S C. Event classification for vehicle navigation system by regional optical flow analysis[J]. Machine Vision and Applications, 2014, 25 (3): 547-559. doi: 10.1007/s00138-011-0384-2
|
[5] |
高韬, 刘正光, 岳士宏, 等. 用于智能交通的运动车辆跟踪算法[J]. 中国公路学报, 2010, 23 (3): 89-94. doi: 10.3969/j.issn.1001-7372.2010.03.014
GAO Tao, LIU Zheng-guang, YUE Shi-hong, et al. Moving vehicle tracking algorithm used for intelligent traffic[J]. China Journal of Highway and Transport, 2010, 23 (3): 89-94. (in Chinese). doi: 10.3969/j.issn.1001-7372.2010.03.014
|
[6] |
TEOHS S, BRÄUNL T. Symmetry-based monocular vehicle detection system[J]. Machine Vision and Applications, 2012, 23 (5): 831-842. doi: 10.1007/s00138-011-0355-7
|
[7] |
LALIMI M A, GHOFRANI S, MCLERNON D et al. A vehicle license plate detection method using region and edge based methods[J]. Computers and Electrical Engineering, 2013, 39 (3): 834-845. doi: 10.1016/j.compeleceng.2012.09.015
|
[8] |
LONG W, YANG Y H. Stationary background generation: an alternative to the difference of two images[J]. Pattern Recognition, 1990, 23 (12): 1351-1359. doi: 10.1016/0031-3203(90)90081-U
|
[9] |
田军, 魏振华, 武思远. 能量法的自适应背景更新算法[J]. 计算机科学与探索, 2009, 3 (2): 218-224. doi: 10.3778/j.issn.1673-9418.2009.02.010
TIAN Jun, WEI Zhen-hua, WU Si-yuan. A self-adaptive background updating algorithm of energy method[J]. Journal of Frontiers of Computer Science and Technology, 2009, 3 (2): 218-224. (in Chinese). doi: 10.3778/j.issn.1673-9418.2009.02.010
|
[10] |
李喜来, 李艾华, 白向峰. 智能交通系统运动车辆的光流法检测[J]. 光电技术应用, 2010, 25 (2): 75-78. doi: 10.3969/j.issn.1673-1255.2010.02.021
LI Xi-lai, LI Ai-hua, BAI Xiang-feng. Moving vehicles detection in intelligent transportation systems based on optical flow[J]. Electro-Optic Technology Application, 2010, 25 (2): 75-78. (in Chinese). doi: 10.3969/j.issn.1673-1255.2010.02.021
|
[11] |
梁敏健, 崔啸宇, 宋青松, 等. 基于HOG-Gabor特征融合与Softmax分类器的交通标志识别方法[J]. 交通运输工程学报, 2017, 17 (3): 151-158. http://transport.chd.edu.cn/article/id/201703016
LIANG Min-jian, CUI Xiao-yu, SONG Qing-song, et al. Traffic sign recognition method based on HOG-Gabor feature fusion and Softmax classifier[J]. Journal of Traffic and Transportation Engineering, 2017, 17 (3): 151-158. (in Chinese). http://transport.chd.edu.cn/article/id/201703016
|
[12] |
AHONEN T, HADID A, PIETIKÄINEN M. Face description with local binary patterns: application to face recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28 (12): 2037-2041. doi: 10.1109/TPAMI.2006.244
|
[13] |
SIVARAMAN S, TRIVEDI M M. Active learning for on-road vehicle detection: a comparative study[J]. Machine Vision and Applications, 2014, 25 (3): 599-611. doi: 10.1007/s00138-011-0388-y
|
[14] |
王永忠, 梁彦, 潘泉, 等. 基于自适应混合高斯模型的时空背景建模[J]. 自动化学报, 2009, 35 (4): 371-378. https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO200904008.htm
WANG Yong-zhong, LIANG Yan, PAN Quan, et al. Spatiotemporal background modeling based on adaptive mixture of Gaussians[J]. Acta Automatica Sinica, 2009, 35 (4): 371-378. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO200904008.htm
|
[15] |
金立生, 王岩, 刘景华, 等. 基于Adaboost算法的日间前方车辆检测[J]. 吉林大学学报: 工学版, 2014, 44 (6): 1604-1608. https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY201406011.htm
JIN Li-sheng, WANG Yan, LIU Jing-hua, et al. Front vehicle detection based on Adaboost algorithm in daytime[J]. Journal of Jilin University: Engineering and Technology Edition, 2014, 44 (6): 1604-1608. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY201406011.htm
|
[16] |
徐姗姗, 刘应安, 徐昇. 基于卷积神经网络的木材缺陷识别[J]. 山东大学学报: 工学版, 2013, 43 (2): 23-28. https://www.cnki.com.cn/Article/CJFDTOTAL-SDGY201302006.htm
XU Shan-shan, LIU Ying-an, XU Sheng. Wood defects recognition based on the convolutional neural network[J]. Journal of Shandong University: Engineering Science, 2013, 43 (2): 23-28. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-SDGY201302006.htm
|
[17] |
丁松涛, 曲仕茹. 基于深度学习的交通目标感兴趣区域检测[J]. 中国公路学报, 2018, 31 (9): 167-174. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL201809020.htm
DING Song-tao, QU Shi-ru. Traffic object detection based on deep learning with region of interest selection[J]. China Journal of Highway and Transport, 2018, 31 (9): 167-174. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL201809020.htm
|
[18] |
LIM K, HONG Y, CHOI Y, et al. Real-time traffic sign recognition based on a general purpose GPU and deeplearning[J]. Plos One, 2017, 12 (3): 1-22.
|
[19] |
TANAKA M, MORIE T. Shadow detection and elimination using a light-source color vector and its application to invehicle camera images[J]. International Journal of Innovative Computing, Information and Control, 2015, 11 (3): 865-879.
|
[20] |
HE Kai-ming, ZHANG Xiang-yu, REN Shao-qing, et al. Delving deepintorectifiers: surpassinghuman-level performance on imagenet classification[C]//IEEE. 15th IEEE International Conference on Computer Vision. New York: IEEE, 2015: 1026-1034.
|
[21] |
SZEGEDY C, TOSHEV A, ERHAN D. Deep neural networks for object detection[C]//Neural Information Processing Systems Foundation. 27th Annual Conference on Neural Information Processing Systems. La Jolla: Neural Information Processing Systems Foundation, 2013: 1-9.
|
[22] |
GIRSHICK R, DONAHUE J, DARRELL T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]//IEEE. 27th IEEE Conference on Computer Vision and Pattern Recognition. New York: IEEE, 2014: 1-21.
|
[23] |
UIJLINGS J R R, VAN DE SANDE K E A, GEVERS T, et al. Selective search for object recognition[J]. International Journal of Computer Vision, 2013, 104 (2): 154-171.
|
[24] |
GIRSHICK R. Fast R-CNN[C]//IEEE. 15th IEEE International Conference on Computer Vision. New York: IEEE, 2015: 1440-1448.
|
[25] |
REN Shao-qing, HE Kai-ming, GIRSHICK R, et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39 (6): 1137-1149.
|
[26] |
REDMON J, DIVVALA S, GIRSHICK R, et al. You only look once: unified, real-time object detection[C]//IEEE. 29th IEEE Conference on Computer Vision and Pattern Recognition. New York: IEEE, 2016: 779-788.
|
[27] |
AHONEN T, HADID A, PIETIKÄINEN M. Face description with local binary patterns: application to face recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28 (12): 2037-2041.
|
[28] |
DONG Jing-wei, SUN Mei-ting, LIANG Geng-rui, et al. The improved neural network algorithm of license plate recognition[J]. International Journal of Signal Processing, Image Processing and Pattern Recognition, 2015, 8 (5): 49-54.
|
[29] |
梁琳, 何卫平, 雷蕾, 等. 光照不均图像增强方法综述[J]. 计算机应用研究, 2010, 27 (5): 1625-1628. https://www.cnki.com.cn/Article/CJFDTOTAL-JSYJ201005008.htm
LIANG Lin, HE Wei-ping, LEI Lei, et al. Survey on enhancement methods for non-uniform illumination image[J]. Application Research of Computers, 2010, 27 (5): 1625-1628. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSYJ201005008.htm
|
[30] |
LI Xun, ZHAO Zheng-fan, LIU Li, et al. An optimization model of multi-intersection signal control for trunk road under collaborative information[J]. Journal of Control Science and Engineering, 2017, 2017: .
|