A low-complexity sensor fusion algorithm based on a fiber-optic gyroscope aided camera pose estimation system

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• 作者：Zhongwei Tan ; Chuanchuan Yang ; Yuliang Li ; Yan Yan…
• 刊名：SCIENCE CHINA Information Sciences
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：59
• 期：4
• 全文大小：1,174 KB
• 刊物类别：Computer Science
• 刊物主题：Chinese Library of Science
  Information Systems and Communication Service
  
• 出版者：Science China Press, co-published with Springer
• ISSN：1869-1919
• 卷排序：59

文摘

Visual tracking, as a popular computer vision technique, has a wide range of applications, such as camera pose estimation. Conventional methods for it are mostly based on vision only, which are complex for image processing due to the use of only one sensor. This paper proposes a novel sensor fusion algorithm fusing the data from the camera and the fiber-optic gyroscope. In this system, the camera acquires images and detects the object directly at the beginning of each tracking stage; while the relative motion between the camera and the object measured by the fiber-optic gyroscope can track the object coordinate so that it can improve the effectiveness of visual tracking. Therefore, the sensor fusion algorithm presented based on the tracking system can overcome the drawbacks of the two sensors and take advantage of the sensor fusion to track the object accurately. In addition, the computational complexity of our proposed algorithm is obviously lower compared with the existing approaches (86% reducing for a 0.5 min visual tracking). Experiment results show that this visual tracking system reduces the tracking error by 6.15% comparing with the conventional vision-only tracking scheme (edge detection), and our proposed sensor fusion algorithm can achieve a long-term tracking with the help of bias drift suppression calibration.Keywordsvisual trackingcamera pose estimationfiber-optic gyroscopelow-complexitysensor fusion