A multi-target detection and recognition approach based on feature-matching of Multilayer Laserscanner

摘要

The article presents a clustering algorithm based on feature-matching of Multilayer Laserscanner to solve false alarm caused by slopes or low interfering objects in the complex urban environment. The experiments show this method can filter non-target points in scene and access to the real targets effectively. To solve multi-target recognition on the road, this article uses a method which combines binary tree structure and high-precision binary classifier based on Adaboost to transform multi-target classification into a series of binary ones. The experimental results show that both target detection algorithm and recognition algorithm are stable and work well in detecting and recognizing pedestrians or vehicles on the road.