Multiple people extraction using 3D range sensor

We propose a novel system for extracting multiple people in crowded scenes by employing LED 3D range sensor. This new kind of device can capture depth image at a relatively high frame speed, which makes the extraction of dynamic objects possible. However, it suffers from the strong noise caused by the environment illumination. Here we propose a novel method for multiple people extraction by integrating an improved version of mean-shift clustering algorithm and total variation based denoising technique. When handling the depth image, it is considered both as a point cloud as well as a 2D image. In this way, different properties of the depth image are sufficiently exploited. The proposed method can fully automatically extract multiple people in a cluttered environment, even from a mobile platform. The experiment conducted at the platform of a railway station demonstrates the effectiveness of our proposed algorithm.