Vehicle Flow Detection Based on Improved Deep Structure and Deep Sort

Real-time vehicle detection based traffic monitoring is a hot research topic within the area of computer vision. In view of the problem of low detection accuracy and low processing speed, a vehicle detection method based on Improved Deep Structure is proposed in this study. Due to the characteristics of highway vehicles with a fixed aspect ratio, k-means ++ clustering method is used to select new anchor boxes to eliminate false targets at an early stage followed by improved depth structure with deep sort. Experimental results demonstrated that our proposed method on standard data set KITTI-UA achieved higher precision and faster speed than the existing algorithms.