Vision-based parking assistance system for leaving perpendicular and angle parking lots

Backing-out maneuvers in perpendicular or angle parking lots are one of the most dangerous maneuvers, specially in cases where side parked cars block the driver view of the potential traffic flow. In this paper a new vision-based Advanced Driver Assistance System (ADAS) is proposed to automatically warn the driver in such scenarios. A monocular gray-scale camera is installed at the back-right side of the vehicle. A Finite State Machine (FSM) defined according to three CAN-Bus variables and a manual signal provided by the user is used to handle the activation/deactivation of the detection module. The proposed oncoming traffic detection module computes spatiotemporal images from a set of pre-defined scan-lines which are related to the position of the road. A novel spatio-temporal motion descriptor is proposed (STHOL) accounting the number of lines, their orientation and length of the spatio-temporal images. A Bayesian framework is used to trigger the warning signal using multivariate normal density functions. Experiments are conducted on image data captured from a vehicle parked at different locations of an urban environment, including different lighting conditions. We demonstrate that the proposed approach provides robust results maintaining processing rates close to real-time.