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Real-time recognition of U.S. speed signs

Christoph Gustav Keller, Christoph Sprunk, Claus Bahlmann, Jan Giebel, Gregory Baratoff
2008 2008 IEEE Intelligent Vehicles Symposium  
In this paper a camera-based system for detection, tracking, and classification of U.S. speed signs is presented.  ...  Classification results from tracked candidates are utilized to improve recognition accuracy. On a standard PC the system reached a detection speed of 27fps with an accuracy of 98.8%.  ...  From an application perspective, the system needs to be adapted for the task of recognizing variable U.S speed limits and other rectangular shaped signs.  ... 
doi:10.1109/ivs.2008.4621282 fatcat:zsgai6p7ife3fjqwagqvrqbwi4

Traffic sign detection for U.S. roads: Remaining challenges and a case for tracking

Andreas Mogelmose, Dongran Liu, Mohan M. Trivedi
2014 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)  
For speed limit signs, the story is different. Detection rates a abysimally low. Clearly, the model is not able to capture what distinguished the speed limit signs from everything else.  ...  We have tested it on video sequences of driving taken from the LISA Traffic Sign Dataset Extension. The sequences cover a total of 139 physical signs.  ... 
doi:10.1109/itsc.2014.6957882 dblp:conf/itsc/MogelmoseLT14 fatcat:j2qnru2zcbh5fbt26he74mdyae

A Study on Traditional and CNN Based Computer Vision Sensors for Detection and Recognition of Road Signs with Realization for ADAS [chapter]

Vinay M. Shivanna, Kuan-Chou Chen, Bo-Xun Wu, Jiun-In Guo
2021 Vision Sensors [Working Title]  
The aim of this chapter is to provide an overview of how road signs can be detected and recognized to aid the ADAS applications and thus enhance the safety employing digital image processing and neural  ...  As per the data from the U.S.  ...  Figure 35 shows the experimental results of the speed limit road signs detection and recognition method for detection and recognition of the rectangular speed limit road signs.  ... 
doi:10.5772/intechopen.99416 fatcat:heripuqk4jdd5ig5j5sw3kuavy

Vision-Based Traffic Sign Detection and Analysis for Intelligent Driver Assistance Systems: Perspectives and Survey

A. Mogelmose, M. M. Trivedi, T. B. Moeslund
2012 IEEE transactions on intelligent transportation systems (Print)  
In this paper, we provide a survey of the traffic sign detection literature, detailing detection systems for traffic sign recognition (TSR) for driver assistance.  ...  We separately describe the contributions of recent works to the various stages inherent in traffic sign detection: segmentation, feature extraction, and final sign detection.  ...  Martin, and E. Ohn-Bar for their comments.  ... 
doi:10.1109/tits.2012.2209421 fatcat:qhln2evg45cjvafipsd4ug7zfe

A complete system to determine the speed limit by fusing a GIS and a camera

Anne-Sophie Puthon, Fawzi Nashashibi, Benazouz Bradai
2011 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)  
Circles are first detected in images with the Hough Transform method. The recognition step aims at separating real speed signs from the other circular shapes.  ...  system to detect traffic signs, eventual supplementary signs and markings; • a decisional part which fuses the information from both sources and outputs the most likely speed limit.  ... 
doi:10.1109/itsc.2011.6082951 dblp:conf/itsc/PuthonNB11 fatcat:3bzpqtemandsxbpb2btg5j33xy

Detection of U.S. Traffic Signs

Andreas Mogelmose, Dongran Liu, Mohan Manubhai Trivedi
2015 IEEE transactions on intelligent transportation systems (Print)  
We go over the recent advances in traffic sign detection and discuss the differences in signs across the world.  ...  Until now, the research in Traffic Sign Recognition systems has been centered on European traffic signs, but signs can look very different across different parts of the world, and a system which works  ...  ACKNOWLEDGMENT The authors would like to thank their colleagues at the LISA lab for useful discussion and encouragement, especially Eshed Ohn-Bar for his valuable comments.  ... 
doi:10.1109/tits.2015.2433019 fatcat:5e37msoczfbp3c266iuuskmey4

Ongoing work on traffic lights: Detection and evaluation

Mark P. Philipsen, Morten B. Jensen, Mohan M. Trivedi, Andreas Mogelmose, Thomas B. Moeslund
2015 2015 12th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)  
Research in traffic light recognition (TLR) has stagnated compared to related computer vision areas, such as pedestrian detection and and traffic sign recognition.  ...  From surveying existing work it is clear that currently evaluation is limited primarily to small local datasets.  ...  Unlike for sign recognition and pedestrian detection, no surveys of TLR research exist.  ... 
doi:10.1109/avss.2015.7301730 dblp:conf/avss/PhilipsenJTMM15 fatcat:4zufhmjmtfgzxf2kwxdbf72dgm

Visual Analysis in Traffic & Re-identification [article]

Andreas Møgelmose
2015 Ph.d.-serien for Det Teknisk-Naturvidenskabelige Fakultet, Aalborg Universitet  
Sujitha Martin, and Mr. Eshed Ohn-Bar for their comments.  ...  Acknowledgment The authors would like to thank their colleagues at the LISA lab for useful discussion and encouragement, especially Eshed Ohn-Bar for his valuable comments.  ...  Image source: [58] Examples of similar signs from the MUTCD. (a) Speed limit. Sign R2-1. (b) Minimum speed. Sign R2-4. (c) End speed limit. Sign R3 (CA), exists only in the California MUTCD.  ... 
doi:10.5278/vbn.phd.engsci.00026 fatcat:taivrerts5debi734ddeeaq244

Neural network-based traffic sign detection and recognition in HD images based on region focusing and parallelization

Aleksej Avramovic, Davor Sluga, Domen Tabernik, Danijel Skocaj, Vladan Stojnic, Nejc Ilc
2020 IEEE Access  
Traffic signs of this type give information about speed limits, priorities, and prohibitions.  ...  speed limits (type X in Fig. 1 ).  ... 
doi:10.1109/access.2020.3031191 fatcat:hh2yqy7eenesxd2wnjwzk7fef4

Note on Attacking Object Detectors with Adversarial Stickers [article]

Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Dawn Song, Tadayoshi Kohno, Amir Rahmati, Atul Prakash, Florian Tramer
2018 arXiv   pre-print
In this note, we briefly show both static and dynamic test results.  ...  Deep learning has proven to be a powerful tool for computer vision and has seen widespread adoption for numerous tasks.  ...  For example, a slight modification to some pixels in Stop sign image can cause a network to label it as a Speed Limit sign.  ... 
arXiv:1712.08062v2 fatcat:hrtmig425zb5ha73cibjyamkv4

Overview of Environment Perception for Intelligent Vehicles

Hao Zhu, Ka-Veng Yuen, Lyudmila Mihaylova, Henry Leung
2017 IEEE transactions on intelligent transportation systems (Print)  
A special attention is paid to methods for lane and road detection, traffic sign recognition, vehicle tracking, behavior analysis, and scene understanding.  ...  Index Terms-Intelligent vehicles, environment perception and modeling, lane and road detection, traffic sign recognition, vehicle tracking and behavior analysis, scene understanding.  ...  Warning Red, White, Black Circle China Warning Red, White, Black Circle Europe SPEED LIMIT Warning Red, White, Black Circle U.S.  ... 
doi:10.1109/tits.2017.2658662 fatcat:mvfmou6ydjafnjq3ddk5rqi5ia

Computer vision in roadway transportation systems: a survey

Robert P. Loce, Edgar A. Bernal, Wencheng Wu, Raja Bala
2013 Journal of Electronic Imaging (JEI)  
There are many interesting technical challenges including imaging under a variety of environmental and illumination conditions, data overload, recognition and tracking of objects at high speed, distributed  ...  Video imaging scientists are providing intelligent sensing and processing technologies for a wide variety of applications and services.  ...  Acknowledgments The authors thank Natesh Manikoth of the Federal Aviation Administration for his insights and many valuable conversations.  ... 
doi:10.1117/1.jei.22.4.041121 fatcat:chkul4gryvawrbxhaagxhkrita

Object fingerprints for content analysis with applications to street landmark localization

Wen Wu, Jie Yang
2008 Proceeding of the 16th ACM international conference on Multimedia - MM '08  
To evaluate, we have compiled a novel dataset which consists of 15 U.S. street landmarks' images and videos.  ...  In particular, we focus on the problem of street landmark localization from images.  ...  Another contribution of this work is a way to deal with object recognition and localization with very limited training data. We have focused on single landmark recognition from images.  ... 
doi:10.1145/1459359.1459383 dblp:conf/mm/WuY08 fatcat:ehwfmx6zpvgbza3d334ltnfxz4

Recognizing temporary changes on highways for reliable autonomous driving

Young-Woo Seo, David Wettergreen, Wende Zhang
2012 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)  
Our approach filters out irrelevant image regions, localizes potential sign image regions using a learned color model, and recognizes signs through classification.  ...  To handle potential recognition errors, our method utilizes the temporal redundancy of sign occurrences and their corresponding classification decisions.  ...  To handle such potential sign recognition errors, we devise two algorithms that utilize the sequence of previous sign classifications.  ... 
doi:10.1109/icsmc.2012.6378255 dblp:conf/smc/SeoWZ12 fatcat:43oqyd2zobdufo6qdmucijgami

Visual surveillance in maritime port facilities

Mikel D. Rodriguez Sullivan, Mubarak Shah, Zia-ur Rahman, Stephen E. Reichenbach, Mark A. Neifeld
2008 Visual Information Processing XVII  
In this work we propose a method for securing port facilities which uses a set of video cameras to automatically detect various vessel classes moving within buffer zones and off-limit areas.  ...  Our approach does not require foreground/background modeling in order to detect vessels, and therefore it is effective in the presence of the class of dynamic backgrounds, such as moving water, which are  ...  Vessel detections are flagged as being potential intruders if no corresponding Figure 9 . A series of frames from a testing sequence.  ... 
doi:10.1117/12.777645 dblp:conf/spieVIP/SullivanS08 fatcat:vtx67xrp4betvbq2xeia2t6qaq
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