ADAS functions are developing really fast and becoming more and more pervasive. The development process is shifting as a result and many are looking at common frameworks that they can leverage to enhance and develop their portfolio of ADAS functions. Many of these require a lot of image/video processing (e.g.: Driver Drowsiness Detection, Pedestrian , Lane Departure Warning, Road Sign Recognition, Pedestrian Detection System, etc) and would benefit from having access to the GPU. OpenCV has the ability to use OpenCL which is a Khronos standard and is implemented by a variety of devices (CPUs, GPUs, FPGAs, ARM), abstracting the exact hardware details, while enabling vendors to provide native implementation for maximal acceleration on their hardware. This project will focus on automotive use-cases and look at enhancing the existing backend to provide a more optimized framework