A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Vehicle detection based on distributed sensor decision fusion
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.
Vehicle detection based on distributed sensor decision fusion
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.
Vehicle detection based on distributed sensor decision fusion
Bin Li, (author) / Rongben Wang, (author) / Keyou Guo, (author)
2002-01-01
393689 byte
Conference paper
Electronic Resource
English
VEHICLE DETECTION BASED ON DISTRIBUTED SENSOR DECISION FUSION
| British Library Conference Proceedings | 2002
Distributed Sensor Fusion in Water Quality Event Detection
| Online Contents | 2011
Distributed Sensor Fusion in Water Quality Event Detection
| British Library Online Contents | 2011
Information Fusion in Distributed Sensor Network for Structural Damage Detection
| British Library Conference Proceedings | 2004