Multi-feature vehicle detection using feature selection

Feature selection has received attention recently in the field of object detection. A vehicle detection method using feature selection is presented in this work. An efficient feature subset is selected using feature selection methods and each feature subset is evaluated by computing the average error rate in different classification methods. The feature selection methods used in this work are the logistic regression, least absolute shrinkage and selection operator (LASSO) and the random forest (RF) methods. The proposed method is evaluated using actual data, showing good performance.