Object classification for LIDAR data using encoded features

Object classification is an important task in vision-based systems. In this work, an intelligent system to perform detection and classification of road objects is presented. The proposed method utilize machine learning algorithm to classify group of points into various categories that represent several road objects. This classification system was trained using 50 features of 2D laser point which were encoded into smaller dimension in order to obtain efficiency. The method was evaluated on public dataset and the experiment results shows that the proposed method achieve quality improvements compared to the baseline. Comparison of several machine learning methods for object classification is also presented to emphasize the superiority of this proposed method.