Moving object detection is a major research direction of video surveillance systems. This paper proposes a novel approach for moving object detection by fusing information from the laser scanner and infrared camera. First, in accordance with the feature of laser scanner data, we apply robust principal component analysis (RPCA) to studying moving object detection. Then the depth and angle information of moving objects is mapped to the infrared image pixels so as to obtain the regions of interest (ROI). Finally, moving objects can be recognized by making investigation of the ROI. Experimental results show that this method has good real-time performance and accuracy.