A real-time detector for parked vehicles based on hybrid background modeling

In this paper, a real-time detection system based on hybrid background modeling is proposed for detecting parked vehicles along the side of a road. The hybrid background model consists of three components: (1) a scene background model, (2) a computed restricted area map, and (3) a dynamic threshold curve for vehicles. By exploiting the motion information of normal activity in the scene, we propose a hybrid background model that determines the location of the road, estimates the roadside and generates the adaptive threshold of the vehicle size. The system triggers a notification when a large vehicle-like foreground object has been stationary for more than a pre-set number of video frames (or time). The proposed method is tested on the AVSS 2007 PV dataset. The results are satisfactory compared to other state-of-the-art methods. (C) 2016 Elsevier Inc. All rights reserved.