A real time 3D sensor for smart cameras

Thank to the widespread diffusion of RGBD sensing devices based on active technologies, in recent years, many research and industrial applications have taken advantage of reliable cues computed from dense depth data. However, although these sensors can be very effective in many circumstances, they are not always well suited for outdoor environments and can also interfere with each other when sensing the same area. On the other hand, traditional systems based on passive stereo vision technology, due to their computational/energy requirements, reliability, size, cost etc, have been, so far, mostly confined to research projects. Nevertheless, recent advances in computation architectures and algorithms enable to overcome most of these issues and, in this paper, we describe the architecture and the processing pipeline of an effective RGBD sensor based on stereo vision suited for real time applications. This sensor allows us to infer, in indoor and outdoor environments, dense and accurate depth maps computed according to state-of-art algorithms and with minimal energy requirements that fit with typical constraints of smart camera systems.