Publication:
Estimation and prediction of the vehicle's motion basedon visual odometry and Kalman filter

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ISSN: 0302-9743
ISBN: 978-3-642-33139-8 (print)
ISBN: 978-3-642-33140-4 (online)
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2012
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Springer
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Abstract
The movement of the vehicle is an useful information for different applications, such as driver assistant systems or autonomous vehicles. This information can be known by different methods, for instance, by using a GPS or by means of the visual odometry. However, there are some situations where both methods do not work correctly. For example, there are areas in urban environments where the signal of the GPS is not available, as tunnels or streets with high buildings. On the other hand, the algorithms of computer vision are affected by outdoor environments, and the main source of difficulties is the variation in the ligthing conditions. A method to estimate and predict the movement of the vehicle based on visual odometry and Kalman filter is explained in this paper. The Kalman filter allows both filtering and prediction of vehicle motion, using the results from the visual odometry estimation.
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Proceeding of: 14th International Conference, ACIVS 2012, Brno, Czech Republic, September 4-7, 2012
Keywords
Stereo vision, Visual odometry, Kalman filter
Bibliographic citation
Advanced concepts for intelligent vision systems: 14th International Conference, ACIVS 2012. Proceedings, Pp. 491-502