OpenCL implementation of motion estimation for cloud video processing

With the raise of cloud computing infrastructures on one side and the increased accessibility of parallel computational devices on the other, such as GPUs and multi-core CPUs, parallel programming has recently gained a renewed interest. This is particularly true in the domain of video coding, where the complexity and time consumption of the algorithms tend to limit the access to the core technology. In this work, we focus on the motion estimation problem, well-known to be the most time consuming step of a majority of video coding techniques. By relying on the use of the OpenCL standard, which provides a cross-platform framework for parallel programming, we propose here a scalable CPU/GPU implementation of the full search motion estimation algorithm (FSBM), and study its performances also with respect to the issues raised by the use of OpenCL.