We present a method to segment dynamic objects on point clouds using images and 3D laser data. Per-pixel background classes are adapted online as Gaussian Mixtures independently for each sensor. The learned classes are fused labeling pixels/voxels that belong to either the background, or the dynamic objects We pay special attention in the calibration and synchronization modules to reach accuracy in registration and data association. We show results of people segmentation in indoor scenes using a Velodyne sensor at a high frame-rate .