Title :
Vehicle detection based on distributed sensor decision fusion
Author :
Li, Bin ; Wang, Rongbcn ; Guo, Kcyou
Author_Institution :
Intelligent Vehicle Res. Groap, Jilin Univ., Changchun, China
Abstract :
Obstacle detection is one of the key functions to intelligent vehicle (IV). In this paper, the recent work of the IV research group of Jilin University of China in detecting the preceding vehicle is introduced. First, a brief overview is given of the vehicle detection approach based on a CCD camera and laser radar, respectively. Then a new vehicle detection method based on distributed bi-sensor decision fusion is put forward. Based on the minimum Bayesian risk criterion and fuzzy a priori probability and fuzzy cost function, the binary decision fusion rule is established. Experiment results are also presented.
Keywords :
computer vision; computerised navigation; decision theory; fuzzy set theory; intelligent control; laser beam applications; probability; road vehicles; sensor fusion; Bayesian risk criterion; CCD camera; Jilin University; distributed sensor decision fusion; fuzzy cost function; fuzzy probability; intelligent vehicle; laser radar; road vehicles; vehicle detection; Bayesian methods; Charge coupled devices; Charge-coupled image sensors; Intelligent sensors; Intelligent vehicles; Laser fusion; Laser radar; Radar detection; Sensor fusion; Vehicle detection;
Conference_Titel :
Intelligent Transportation Systems, 2002. Proceedings. The IEEE 5th International Conference on
Print_ISBN :
0-7803-7389-8
DOI :
10.1109/ITSC.2002.1041222