Title :
Vision based obstacle tracking in urban traffic environments
Author :
Bota, Silviu ; Nedevschi, Sergiu
Author_Institution :
Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania
Abstract :
Stereo vision based sensors provide large amounts of data, a fact which is advantageous when trying to extract semantic information about the imaged scene. However, this data is corrupted by errors, caused especially by the uncertainties in the stereo reconstruction process. Temporal information can be used in order to minimize these errors. This paper presents an advanced object model, a novel association mechanism and the design of a Kalman filter based tracking algorithm, for tracking multiple objects, in complex, urban traffic scenarios.
Keywords :
Kalman filters; computer vision; feature extraction; natural scenes; object tracking; road traffic; stereo image processing; traffic engineering computing; Kalman filter based tracking algorithm; advanced object model; association mechanism; error minimization; multiple object tracking; natural scene; semantic information extraction; stereo reconstruction process; stereo vision based sensor; temporal information; urban traffic environment; vision based obstacle tracking; Adaptive optics; Covariance matrix; Kalman filters; Optical imaging; Optical sensors; Prediction algorithms; Vehicles;
Conference_Titel :
Intelligent Computer Communication and Processing (ICCP), 2011 IEEE International Conference on
Conference_Location :
Cluj-Napoca
Print_ISBN :
978-1-4577-1479-5
Electronic_ISBN :
978-1-4577-1481-8
DOI :
10.1109/ICCP.2011.6047874
