Fast approach for moving vehicle localization and bounding box estimation in highway traffic videos

Abstract

Detection and accurate localization of position of moving vehicles in a video sequence are the primary tasks in every computer vision-based traffic monitoring system. In this paper, a moving vehicle localization and bounding box estimation algorithm is proposed. The moving vehicle foreground is separated from the static background by the adaptive background subtraction method, and the bounding box of moving vehicles is estimated with two-dimensional binary histogram projection profile (2D-BHPP) algorithm. The foreground object refinement is performed by means of morphological closing operation prior to apply the 2D-BHPP algorithm. The proposed method only computes the four necessary minimum bounding box coordinates, i.e., left, right, upper, and lower of moving vehicles in every frame. The proposed method is tested over three publicly available data sets, and the results show that the localization algorithm works comparatively faster and accurately than the existing localization methods. The detection error rate, IoU metric, and execution time per frame signify that this approach can be implemented in edge-based real-time applications.