People tracking is a crucial component of many intelligent video surveillance systems and recent developments in embedded computing architectures and algorithms allow us to design compact, lightweight and energy efficient systems aimed at tackling this problem. In particular, the advent of cheap RGBD sensing devices enables to exploit depth information as additional cue. In this paper we propose a 3D tracking system aimed to become the basic node of a distributed system for business analytics applications. In the envisioned distributed system each node would consist of a custom stereo camera with on-board FPGA processing coupled with a compact CPU based board. In the basic node proposed in this paper, aimed at raw people tracking within the sensed area of a single device, the custom stereo camera delivers, in real time and with minimal energy requirements, accurate dense depth maps according to state-of-the-art computer vision algorithms. Then, the CPU based system, by processing this information enables reliable 3D people tracking. In our system, deploying the FPGA front-end, the main constraint for real time 3D tracking is concerned with the computing requirement of the CPU based board and, in this paper, we propose a fast and effective node for 3D people tracking algorithm suited for implementation on embedded devices.