ITS 2011 - Special Issue: Machine Learning for Traffic Sign Recognition

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Category ITS 2011

Deadline: October 15, 2011 | Date: December 15, 2011

Venue/Country: Call for Papers, Online

Updated: 2011-07-20 07:36:02 (GMT+9)

Call For Papers - CFP

Machine Learning for Traffic Sign Recognition

Recognition of traffic signs is a challenging real-world problem

relevant for intelligent transportation systems. It is a

multi-category classification problem with unbalanced class

frequencies. Traffic signs show a wide range of variations between

classes in terms of color, shape, and the presence of pictograms or

text. However, there exist subsets of classes (e.g., speed limit

signs) that are very similar to each other. Further, the classifier

has to cope with large variations in visual appearances due to

illumination changes, partial occlusions, rotations, weather

conditions etc.

Although first commercial systems have reached the market and several

studies on sign recognition have been published, systematic

comparisons of different approaches are scarce.

The special issue focuses on unbiased evaluation of new and existing

methods from computer vision, machine learning, and related fields for

traffic sign recognition. Empirical evaluation should be based on

freely available benchmark data.

The special issue is organized in the context of the German Traffic

Sign Recognition Benchmark (GTSRB), a competition at this year's IEEE

International Conference on Artificial Neural Networks (IJCNN 2011).

The GTSRB data is freely available from http://benchmark.ini.rub.de,

the final test data will be released in August.

Important dates

Manuscript submissions due: October 15 2011:

Notification of acceptance: November 20 2011

Revised manuscripts due: December 15 2011

Publication: second issue 2012

Submission

Manuscripts should be submitted at

http://mc.manuscriptcentral.com/t-its by selecting the manuscript type

`Special Issue on MLFTSR'.

Special issue editors

Johannes Stallkamp, Ruhr-Universität Bochum, Germany

Marc Schlipsing, Ruhr-Universität Bochum, Germany

Jan Salmen, Ruhr-Universität Bochum, Germany

Christian Igel, University of Copenhagen, Denmark

Contact

tsr-benchmarkini.ruhr-uni-bochum.de

--

Johannes Stallkamp

Lehrstuhl Theorie kognitiver Systeme

Institut für Neuroinformatik

Ruhr-Universität Bochum

44780 Bochum, Germany

office: NB 3 / 71

tel: +49 234 32 25566

fax: +49 234 32 14209

email: Johannes.Stallkampini.ruhr-uni-bochum.de

URL: http://www.ini.ruhr-uni-bochum.de