A Novel Monocular Visual Odometer Method Based on Kinect and Improved SURF Algorithm

Abstract

The paper proposes a novel monocular visual odometer method based on Kinect sensor made by Microsoft and the improved SURF algorithm. Firstly the Kinect sensor capture color images and depth images of the surrounding environment, then we use the improved SURF algorithm to extract feature points of the color images and match for them. At last, map what we get with the depth image and estimate the path information of the robot by doing 3D reconstruction and using the the least square mean value theorem. Experimental results show that by using this new method, the average matching accuracy reaches 92.6%. And even in a dynamic environment, it shows good robustness, so it comes down to the conclusion that the combination of the Kinect sensor and the improved SURF algorithm applied to visual odometer is a simple and effective method.