Video-based self-positioning for intelligent transportation systems applications

Parag S. Chandakkar, Ragav Venkatesan, Baoxin Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Many urban areas face traffic congestion. Automatic traffic management systems and congestion pricing are getting prominence in recent research. An important stage in such systems is lane prediction and on-road self-positioning. We introduce a novel problem of vehicle self-positioning which involves predicting the number of lanes on the road and localizing the vehicle within those lanes, using the video captured by a dashboard camera. To overcome the disadvantages of most existing low-level vision-based techniques while tackling this complex problem, we formulate a model in which the video is a key observation. The model consists of the number of lanes and vehicle position in those lanes as parameters, hence allowing the use of high-level semantic knowledge. Under this formulation, we employ a lane-width-based model and a maximum-likelihoodestimator making the method tolerant to slight viewing angle variation. The overall approach is tested on real-world videos and is found to be effective.

Original languageEnglish (US)
Title of host publicationAdvances in Visual Computing - 10th International Symposium, ISVC 2014, Proceedings
EditorsJason Jerald, George Bebis, Bahram Parvin, Zhigang Deng, Richard Boyle, El Choubassi Maha, Hui Zhang, Darko Koracin, Ryan McMahan, Steven M. Drucker, Mark Carlson, Kambhamettu Chandra
PublisherSpringer Verlag
Pages718-729
Number of pages12
ISBN (Electronic)9783319142487
StatePublished - Jan 1 2014
Event10th International Symposium on Visual Computing, ISVC 2014 - Las Vegas, United States
Duration: Dec 8 2014Dec 10 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8887
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other10th International Symposium on Visual Computing, ISVC 2014
CountryUnited States
CityLas Vegas
Period12/8/1412/10/14

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Chandakkar, P. S., Venkatesan, R., & Li, B. (2014). Video-based self-positioning for intelligent transportation systems applications. In J. Jerald, G. Bebis, B. Parvin, Z. Deng, R. Boyle, E. C. Maha, H. Zhang, D. Koracin, R. McMahan, S. M. Drucker, M. Carlson, & K. Chandra (Eds.), Advances in Visual Computing - 10th International Symposium, ISVC 2014, Proceedings (pp. 718-729). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8887). Springer Verlag.