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.
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