The recent technological progress is pushing the scientific community for entering a new Artificial Intelligence (AI) era, with systems able to perceive and understand the real world, in order to solve problems in a smarter way than humans do. In this field, Computer Vision (CV) systems are able to automatically see, identify, and understand the external visual world, making decisions depending on the data acquired, emulating the human vision. This progress is placed side by side with a continuous search of hardware architectures, such as GPUs, FPGAs, and ASICs, that can sustain the computation in a more efficient way than conventional software implementations do, allowing the analysis of data directly where it is acquired.