Car parking assistance based on time-or-flight camera

External sensing for automative applications are key tools for the development of Advanced Driver Assistance Systems (ADAS), since they can sense and analyse the environment around the vehicle by providing pictures of the scene behind the vehicle. Parking assistance systems are already available in the market. However, most of these applications are based on ultrasonic sensors, wide-angle image cameras, RADAR, etc, which present some drawbacks such as dependency to light conditions or high maintenance cost, among others. This paper proposes an approach for assisting drivers to park through the processing of data derived by a 3D Time-of-Flight (ToF) camera and the reconstruction of the objects identified around the vehicle. The proposed technique is focused on fusion of two parallel processing technologies, a visual one through the intensity image and a spatial one through the point cloud. Both of them are centered on the detection of the vehicle's plate to estimate its position and determine free spots in the parking. This novel methodology improves the detection of surrounding elements, since it helps to solve two main problems with this kind of devices: 1) the degraded performance under bright ambient light problem (occurring mainly in outdoor parkings), that causes shadows and brightness in the images, hindering its process to detect objects; and 2) the limited detection of low reflection objects such as dark cars. Moreover, this fusion allows to link each pixel of the image with a 3D position, and vice versa, giving the point cloud a visual reference. The system is evaluated through a Renault Twizy platform in real conditions.