We present a method to segment dynamic objects from high-resolution low-rate laser scans. Data points are tagged as static or dynamic based on the classification of pixel data from registered imagery. Per-pixel background classes are adapted online as Gaussian mixtures, and their matching 3D points are classified accordingly. Special attention is paid to the correct calibration and synchronization of the scanner with the the accessory camera. Results of the method are shown for a small indoor sequence with several people following arbitrarily different trajectories.


computer vision, pattern classification, robots.

Scientific reference

A.A. Ortega and J. Andrade-Cetto. Segmentation of dynamic objects from laser data, 5th European Conference on Mobile Robots, 2011, Örebro, Sweden, pp. 115-121, Örebro Univ.