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Recognition of Traffic Sign Based on Bag-of-Words and Artificial Neural Network

2017 Symmetry  
The proposed traffic sign detection and recognition system obtained 99.00% classification accuracy with a 1.00% false positive rate.  ...  A robust artificial intelligence based traffic sign recognition system can support the driver and significantly reduce driving risk and injury.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/sym9080138 fatcat:xofie524pvfnjljoxghxfuir5u

Multi-view traffic sign detection, recognition, and 3D localisation

Radu Timofte, Karel Zimmermann, Luc Van Gool
2009 2009 Workshop on Applications of Computer Vision (WACV)  
The paper proposes a pipeline for the efficient detection and recognition of traffic signs from such images.  ...  For the initial detection in single frames, we use a set of colour-and shape-based criteria. They yield a set of candidate sign patterns.  ...  Acknowledgements This work was supported by the Flemish IBBT-URBAN project and the European Commission FP7-231888-EUROPA project. The authors thank GeoAutomation for providing the images.  ... 
doi:10.1109/wacv.2009.5403121 dblp:conf/wacv/TimofteZG09 fatcat:37ehadoiwjgh5pzuxh7if4o5ce

Construction of a traffic sign detector based on voting type co-training

Yuji Kojima, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase
2013 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)  
In this paper, we employ this approach for improving the accuracy of a traffic sign detector with low cost.  ...  The main contributions of this paper are the extension of the cotraining method by introducing a majority voting scheme, and the introduction of this framework for improving the accuracy of traffic sign  ...  From this point of view, object detection and recognition from invehicle camera images have been widely studied, e.g. for pedestrians [1] , traffic signs [2] , and other targets.  ... 
doi:10.1109/itsc.2013.6728385 dblp:conf/itsc/KojimaDIM13 fatcat:xhx6rr5w3naotcanju2jr26nqq

Colour Vision Model-Based Approach for Segmentation of Traffic Signs

Xiaohong Gao, Kunbin Hong, Peter Passmore, Lubov Podladchikova, Dmitry Shaposhnikov
2008 EURASIP Journal on Image and Video Processing  
of colour-based approach.  ...  This paper presents a new approach to segment traffic signs from the rest of a scene via CIECAM, a colour appearance model.  ...  Their multiple-threshold approach is good for not missing any candidate, but it detects many false candidate regions.  ... 
doi:10.1155/2008/386705 fatcat:xyadufztlrcnxhl2d73c5tatxq

Traffic Sign Detection System for Locating Road Intersections and Roundabouts: The Chilean Case

Gabriel Villalón-Sepúlveda, Miguel Torres-Torriti, Marco Flores-Calero
2017 Sensors  
Templates consider the mean and standard deviation of normalized color of the traffic signs to build thresholding intervals where the expected color should lie for a given sign.  ...  This paper presents a traffic sign detection method for signs close to road intersections and roundabouts, such as stop and yield (give way) signs.  ...  Recognition of Traffic Signs Based on Statistical Templates The second stage of the proposed traffic sign detection approach is responsible for solving the identification of ROIs as traffic signs of a  ... 
doi:10.3390/s17061207 pmid:28587071 pmcid:PMC5492493 fatcat:wqo5ser4d5h2jlurk6umxxpbye

Vision based Traffic Police Hand Signal Recognition in Surveillance Video - A Survey

R. Sathya, M. Kalaiselvi Geetha
2013 International Journal of Computer Applications  
The recognition of human hand gesture movement can be performed at various level of abstraction. This survey concentrate on approaches that aim on recognizing traffic police hand signals.  ...  Many application and algorithms were discussed with the recognition framework. General overview of an traffic control gestures and its various applications where discussed in this paper.  ...  Space time interest point detects subspace of correlated movement instead of detecting interest point over the entire volume.  ... 
doi:10.5120/14037-2192 fatcat:dtns3iu3fje77dnrgsn2346qoq

Exploiting temporal and spatial constraints in traffic sign detection from a moving vehicle

Siniša Šegvić, Karla Brkić, Zoran Kalafatić, Axel Pinz
2011 Machine Vision and Applications  
This paper addresses detection, tracking and recognition of traffic signs in video.  ...  We propose a novel two-stage technique which achieves improved detection results by applying temporal and spatial constraints to the occurrences of traffic signs in video.  ...  Acknowledgements This research has been jointly funded by Croatian National Foundation for Science, Higher Education and Technological Development, and Institute of Traffic and Communications, under programme  ... 
doi:10.1007/s00138-011-0396-y fatcat:mdvnlnn6jrctpc2m2z3c56zbty

Anomaly Detection in Road Traffic Using Visual Surveillance: A Survey [article]

Santhosh Kelathodi Kumaran, Debi Prosad Dogra, Partha Pratim Roy
2019 arXiv   pre-print
Finally, we discuss the challenges in the computer vision related anomaly detection techniques and some of the important future possibilities.  ...  We then summarize the important contributions made during last six years on anomaly detection primarily focusing on features, underlying techniques, applied scenarios and types of anomalies using single  ...  Histogram of optical flow and motion [207] Sub-trajectories Multi instance learning Nearest neighborhood based approach with Hausdorff distance-based threshold for anomaly detection.  ... 
arXiv:1901.08292v1 fatcat:qehtkb2imfbmpfahkgsjrx7544

A Novel Approach to Detect Pedestrian from Still Images Using Random Subspace Method

V.V. Priya, P. Rekha, K.C. Reshmi, S. Manoj kumar, K. Indhulekha
2016 Procedia Technology - Elsevier  
Human detection is the crucial part within the systems of humanistic image reclamation, visual scrutiny, pedestrian detection, and posture recognition, home automation, robot sensing.  ...  To implement these using mainly three types of datasets PobleSec, INRIA and Daimler Multicue dataset, additionally used linear SVM for classification.  ...  Rather than using this classifiers method which uses a fuzzy based approach which is based on choosing the threshold for a particular dataset.  ... 
doi:10.1016/j.protcy.2016.08.115 fatcat:eeda65zzofhd3ns3wyfgzuo7p4

Review on Real Time Background Extraction: Models, Applications, Environments, Challenges and Evaluation Approaches

Maryam A. Yasir, Yossra Hussain Ali
2021 International Journal of Online and Biomedical Engineering (iJOE)  
Background extraction is the most popular technique employed in the domain of detecting moving foreground objects taken by stationary surveillance cameras.  ...  We list the four process stages of background extraction and we consider several well-known models starting with the conventional models and ending up with the state-of-the art models.  ...  and these models are dependable on threshold and are not supporting the multiple model background distributions.  ... 
doi:10.3991/ijoe.v17i02.18013 fatcat:qk4uus56njfy5m2mbvseg6vfue

Challenging Environments for Traffic Sign Detection: Reliability Assessment under Inclement Conditions [article]

Dogancan Temel and Tariq Alshawi and Min-Hung Chen and Ghassan AlRegib
2019 arXiv   pre-print
Therefore, it is not possible to estimate the performance of traffic sign detection algorithms under overlooked challenging conditions.  ...  State-of-the-art algorithms successfully localize and recognize traffic signs over existing datasets, which are limited in terms of challenging condition type and severity.  ...  Therefore, researchers have been heavily focused on designing traffic sign detection and recognition algorithms.  ... 
arXiv:1902.06857v2 fatcat:l5ivrm3oorayxldoj7qe4bhlnq

Adaptive Fuzzy Filter for Speech Enhancement [chapter]

Chih-Chia Yao, Ming-Hsun Tsai
2010 Lecture Notes in Computer Science  
In this paper an adaptive fuzzy filter, based on fuzzy system, is proposed for speech signal enhancement and automatic speech recognition accuracy.  ...  The adaptive threshold and membership functions are optimally obtained by particle swarm optimization algorithm so the SNR of the filter output for training signal data can be maximized.  ...  Therefore, we make use of the same approach to configure and establish the model, and process for recognition. The evaluation of the proposed system includes two parts.  ... 
doi:10.1007/978-3-642-12179-1_42 fatcat:s3sqmtr22fganc725eeuu35pvq

Mono-vision based moving object detection in complex traffic scenes

Vincent Fremont, Sergio Alberto Rodriguez Florez, Bihao Wang
2017 2017 IEEE Intelligent Vehicles Symposium (IV)  
Therefore, moving object detection in complex traffic scene becomes an inevitable issue for ADAS and autonomous vehicles.  ...  Vision-based dynamic objects motion segmentation can significantly help to understand the context around vehicles, and furthermore improve road traffic safety and autonomous navigation.  ...  In this paper, we propose an enhanced geometric constraint-based approach for moving objects detection.  ... 
doi:10.1109/ivs.2017.7995857 dblp:conf/ivs/FremontFW17 fatcat:sgv3vstcq5h3xjm34nrtx55o2y

A Dynamic Hierarchical Clustering Method for Trajectory-Based Unusual Video Event Detection

Fan Jiang, Ying Wu, A.K. Katsaggelos
2009 IEEE Transactions on Image Processing  
Moreover, it iteratively updates the basis of the subspace-which makes it suitable for dealing with sequentially coming data and online learning.  ...  A novel subspace analysis method is reported in this correspondence for feature extraction and dimensionality reduction based on FL distance. The algorithm brings better generalization ability.  ...  ACKNOWLEDGMENT The authors would like to thank the associate editor and all anonymous reviewers for their constructive comments on the first two versions of this paper.  ... 
doi:10.1109/tip.2008.2012070 pmid:19273049 fatcat:6dudswvfobgc3h77zqp6hr6qtq

Object detection and segmentation on a hierarchical region-based image representation

Veronica Vilaplana, Ferran Marq, Miriam Leon, Antoni Gasull
2010 2010 IEEE International Conference on Image Processing  
We illustrate the usefulness of the approach with four different object classes: sky, caption text, traffic signs and faces.  ...  In this paper we present a general framework for object detection and segmentation.  ...  INTRODUCTION The most common approaches to object detection are block-based: the image is scanned at multiple scales with a sliding window of fixed size and shape -typically rectangular-, and the contents  ... 
doi:10.1109/icip.2010.5649967 dblp:conf/icip/VilaplanaMLG10 fatcat:vd37egtf5zcklmvbwuplamrhma
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