document: In Obstacle detection is based on inverse perspective mapping and homography. Obstacle classification is based on fuzzy neural network. The estimation of the vanishing point relies on feature extraction strategy. The method exploits the geometrical relations between the elements in the scene so that obstacle can be detected. The estimated homography of the road plane between successive images is used for image alignment. A new fuzzy decision fusion method with fuzzy attribution for obstacle detection and classification application is described The fuzzy decision function modifies parameters with auto-adapted algorithm to get better classification probability It is shown that the method can achieve better classification result.
doc_bio_tags: O B O O O O B I I I I B B O O O B I I O B I I I I O O B I I O O O O B I O O B O O B O O B O O B O B I O O B I O O B O O O B I O O B I I I O O O O B O O B O O O B I I I O O O O O O O O B O O O O O O O O O O B O
extractive_keyphrases: classification detected elements estimated homography estimation of the vanishing point feature extraction strategy fuzzy decision fusion method fuzzy neural network geometrical relations image alignment images inverse perspective mapping and homography obstacle road plane scene the fuzzy decision function
abstractive_keyphrases: auto-adapted algorithm fuzzy attribution for obstacle detection and classification application obstacle classification obstacle detection obstacle detection and classification application