WO2019042728A3 - Detection of road users on a traffic route - Google Patents
Detection of road users on a traffic route Download PDFInfo
- Publication number
- WO2019042728A3 WO2019042728A3 PCT/EP2018/071494 EP2018071494W WO2019042728A3 WO 2019042728 A3 WO2019042728 A3 WO 2019042728A3 EP 2018071494 W EP2018071494 W EP 2018071494W WO 2019042728 A3 WO2019042728 A3 WO 2019042728A3
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- road users
- traffic route
- detection
- object detection
- suggested regions
- Prior art date
Links
Classifications
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0116—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
- G06V20/54—Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
- G08G1/0145—Measuring and analyzing of parameters relative to traffic conditions for specific applications for active traffic flow control
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
Abstract
The invention relates to a method (10) for detecting road users (12) on a traffic route (14) in an image. Said method comprises the following steps: - creating (42) a plurality of suggested regions (18) for possible objects recorded in the image (16) using a region suggestion generator; - providing object detection (72) for all suggested regions (18) in order to detect the traffic route (14) and/or road users (12) by classification, taking into account a predefined confidence level; - outputting detection data which are received by the object detection; and - providing filtering (48) for the suggested regions (18) prior to the step in which object detection is provided, wherein filtering is performed based on the respective filter data which are estimated based of a relevance of the suggested regions (18) in combination with the road users (12) and/or the traffic route (14).
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE102017215079.3 | 2017-08-29 | ||
DE102017215079.3A DE102017215079A1 (en) | 2017-08-29 | 2017-08-29 | Capturing road users on a traffic route |
Publications (2)
Publication Number | Publication Date |
---|---|
WO2019042728A2 WO2019042728A2 (en) | 2019-03-07 |
WO2019042728A3 true WO2019042728A3 (en) | 2019-04-25 |
Family
ID=63259495
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/EP2018/071494 WO2019042728A2 (en) | 2017-08-29 | 2018-08-08 | Detection of road users on a traffic route |
Country Status (2)
Country | Link |
---|---|
DE (1) | DE102017215079A1 (en) |
WO (1) | WO2019042728A2 (en) |
Families Citing this family (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102019007058A1 (en) | 2019-10-10 | 2021-04-15 | CGF Counsel Group Frankfurt AG | DEVICE WITHIN A MASTER AND PROCEDURE |
DE102019007057B4 (en) | 2019-10-10 | 2022-06-30 | CGF Counsel Group Frankfurt AG | OUTDOOR DEVICE WITH ELECTRONIC COMPONENT |
CN113139427A (en) * | 2021-03-12 | 2021-07-20 | 浙江智慧视频安防创新中心有限公司 | Steam pipe network intelligent monitoring method, system and equipment based on deep learning |
DE102021117613A1 (en) | 2021-07-08 | 2023-01-12 | Valeo Schalter Und Sensoren Gmbh | METHOD OF OPERATING A PARKING ASSISTANCE SYSTEM, COMPUTER PROGRAM PRODUCT AND PARKING ASSISTANCE SYSTEM |
CN113807270A (en) * | 2021-09-22 | 2021-12-17 | 北京百度网讯科技有限公司 | Road congestion detection method and device and electronic equipment |
CN117710795A (en) * | 2024-02-06 | 2024-03-15 | 成都同步新创科技股份有限公司 | Machine room line safety detection method and system based on deep learning |
Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104658279A (en) * | 2015-02-17 | 2015-05-27 | 公安部交通管理科学研究所 | Real-time optimization signal control method and system based on video traffic state monitoring |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2011113444A1 (en) * | 2010-03-15 | 2011-09-22 | Panasonic Corporation | Method and apparatus for trajectory estimation, and method for segmentation |
US9947077B2 (en) * | 2013-12-31 | 2018-04-17 | Thomson Licensing | Video object tracking in traffic monitoring |
JP6604019B2 (en) * | 2015-04-14 | 2019-11-13 | ソニー株式会社 | Image processing apparatus, image processing method, and image processing system |
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2017
- 2017-08-29 DE DE102017215079.3A patent/DE102017215079A1/en active Pending
-
2018
- 2018-08-08 WO PCT/EP2018/071494 patent/WO2019042728A2/en active Application Filing
Patent Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104658279A (en) * | 2015-02-17 | 2015-05-27 | 公安部交通管理科学研究所 | Real-time optimization signal control method and system based on video traffic state monitoring |
Non-Patent Citations (9)
Title |
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"Medical image computing and computer-assisted intervention - MICCAI 2015 : 18th international conference, Munich, Germany, October 5-9, 2015; proceedings", vol. 8691, 1 January 2014, SPRINGER INTERNATIONAL PUBLISHING, Cham, ISBN: 978-3-642-38081-5, ISSN: 0302-9743, article XINGYU ZENG ET AL: "Deep Learning of Scene-Specific Classifier for Pedestrian Detection", pages: 472 - 487, XP055424079, 032548, DOI: 10.1007/978-3-319-10578-9_31 * |
ALA MHALLA ET AL: "SMC faster R-CNN: Toward a scene-specialized multi-object detector", COMPUTER VISION AND IMAGE UNDERSTANDING., vol. 164, 30 June 2017 (2017-06-30), US, pages 3 - 15, XP055521016, ISSN: 1077-3142, DOI: 10.1016/j.cviu.2017.06.008 * |
ANDREAS GEIGER ET AL: "Joint 3D Estimation of Objects and Scene Layout", 1 January 2011 (2011-01-01), XP055520458, Retrieved from the Internet <URL:http://www.cs.utoronto.ca/~urtasun/publications/geiger_et_al_nips11.pdf> [retrieved on 20181031] * |
CHEN XIAOZHI ET AL: "Monocular 3D Object Detection for Autonomous Driving", 2016 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), IEEE, 27 June 2016 (2016-06-27), pages 2147 - 2156, XP033021394, DOI: 10.1109/CVPR.2016.236 * |
JIFENG DAI ET AL: "R-FCN: Object Detection via Region-based Fully Convolutional Networks", IADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS, 21 June 2016 (2016-06-21), XP055486238, Retrieved from the Internet <URL:https://arxiv.org/pdf/1605.06409.pdf> [retrieved on 20180620] * |
LI-WU TSAI ET AL: "Multi-Lane Detection and Road Traffic Congestion Classification for Intelligent Transportation System", ENERGY PROCEDIA, 1 January 2011 (2011-01-01), pages 3174 - 3182, XP055553257, Retrieved from the Internet <URL:https://pdfs.semanticscholar.org/8f30/70c51793f30ea7b6afd1ab1a8c193b9fc7fd.pdf> DOI: 10.1016/j.egypro.2011.11.460 * |
MAYANK BANSAL ET AL: "A real-time pedestrian detection system based on structure and appearance classification", 2010 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION : ICRA 2010 ; ANCHORAGE, ALASKA, USA, 3 - 8 MAY 2010, IEEE, PISCATAWAY, NJ, USA, 3 May 2010 (2010-05-03), pages 903 - 909, XP031743776, ISBN: 978-1-4244-5038-1 * |
SCOTT PENDLETON ET AL: "Perception, Planning, Control, and Coordination for Autonomous Vehicles", MACHINES, vol. 5, no. 1, 17 February 2017 (2017-02-17), pages 6, XP055553408, DOI: 10.3390/machines5010006 * |
WANG XIAOGANG ET AL: "Scene-Specific Pedestrian Detection for Static Video Surveillance", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, IEEE COMPUTER SOCIETY, USA, vol. 36, no. 2, 1 February 2014 (2014-02-01), pages 361 - 374, XP011534231, ISSN: 0162-8828, [retrieved on 20131218], DOI: 10.1109/TPAMI.2013.124 * |
Also Published As
Publication number | Publication date |
---|---|
DE102017215079A1 (en) | 2019-02-28 |
WO2019042728A2 (en) | 2019-03-07 |
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