DocumentCode :
1871872
Title :
On-board robust vehicle detection and tracking using adaptive quality evaluation
Author :
Arróspide, Jon ; Salgado, Luis ; Nieto, Marcos ; Jaureguizar, Fernando
Author_Institution :
Grupo de Tratamiento de Imageries - E. T. S. Ing. Telecomun., Univ. Politec. de Madrid, Madrid
fYear :
2008
fDate :
12-15 Oct. 2008
Firstpage :
2008
Lastpage :
2011
Abstract :
This paper presents a robust method for real-time vehicle detection and tracking in dynamic traffic environments. The proposed strategy aims to find a trade-off between the robustness shown by time-uncorrelated detection techniques and the speed-up obtained with tracking algorithms. It combines both advantages by continuously evaluating the quality of the tracking results along time and triggering new detections to restart the tracking process when quality falls behind a certain quality requirement. Robustness is also ensured within the tracking algorithm with an outlier rejection stage and the use of stochastic filtering. Several sequences from real traffic situations have been tested, obtaining highly accurate multiple vehicle detections.
Keywords :
Kalman filters; image sequences; road vehicles; stochastic processes; tracking; traffic engineering computing; Kalman filtering; adaptive quality evaluation; dynamic traffic environments; on-board robust vehicle detection; optical flow; stochastic filtering; time-uncorrelated detection; vehicle tracking; Feature extraction; Filtering; Image motion analysis; Optical computing; Optical filters; Phase detection; Robustness; Vehicle detection; Vehicle dynamics; Vehicles; Kalman filtering; RANSAC; Vehicle detection; optical flow; tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
Conference_Location :
San Diego, CA
ISSN :
1522-4880
Print_ISBN :
978-1-4244-1765-0
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2008.4712178
Filename :
4712178
Link To Document :
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