DocumentCode
3465960
Title
Vehicle detection fusing 2D visual features
Author
Hoffman, Caio ; Dang, Thao ; Stiller, Christoph
Author_Institution
Inst. fur Mess- und Regelungstech., Karlsruhe Univ., Germany
fYear
2004
fDate
14-17 June 2004
Firstpage
280
Lastpage
285
Abstract
This paper presents a method for detection and tracking of vehicles by finding various characteristic features in the images of a monochrome camera. The detection process uses shadow and symmetry features to generate vehicle hypotheses. These are fused and tracked over time using an Interacting Multiple Model method (IMM). Results for natural traffic scenes demonstrate high reliability of the proposed method.
Keywords
Kalman filters; cameras; feature extraction; filtering theory; object detection; road vehicles; 2D visual feature fusing; interacting multiple model method; monochrome camera; natural traffic scenes; reliability; shadow features; symmetry features; vehicle detection; vehicle hypotheses; vehicle tracking; Cameras; Computer vision; Feature extraction; Filters; Image sequences; Layout; Modems; Sensor phenomena and characterization; Vehicle detection; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Vehicles Symposium, 2004 IEEE
Print_ISBN
0-7803-8310-9
Type
conf
DOI
10.1109/IVS.2004.1336395
Filename
1336395
Link To Document