Moving objects detection using freely moving depth sensing camera

The detection of moving objects for the surveillance and monitoring has been studied in the computer vision community for many years. Traditionally, the studies assume the use of a stationary camera. When using a 3D point cloud, research is restricted to the fixed laser scanner because of the slow data acquisition time. In this paper, we propose a method for detecting moving objects based on a freely moving sensor that provides two-dimensional-three-dimensional(2D-3D) fused data. Our method is a frame-differencing, which compares two consecutive frames combining visual features and a 3D point cloud. The RANSAC and ICP algorithms are applied for more accurate results. The moving objects can be separated in the 3D point cloud by adopting RANSAC outliers.