Rihem El Euch, E. Garcia-Fidalgo, A. Ortiz, F. Chaabane, A. Ghazel
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引用次数: 0
Abstract
Recognizing whether the current place has been visited before or not is an important task in robotic navigation, since it helps to reduce the inconsistencies produced by the inherent noise of navigation sensors. When a camera is used as input for navigation, this process is known as visual loop closure detection. Under this context, in this work we propose a loop closure detection method based on superpixels and a Bag of Words scheme. A novel image description method for superpixels is proposed. Our approach also makes use of the concept of dynamic islands, which allows us to group images close in time and to avoid images taken from the same place to compete among them as loop closure candidates. The proposed method is validated using several outdoor public image sequences and compared to other state-of-the-art solutions.
识别当前位置以前是否被访问过是机器人导航中的一项重要任务,因为它有助于减少导航传感器固有噪声产生的不一致性。当使用相机作为导航输入时,这个过程被称为视觉闭环检测。在此背景下,本文提出了一种基于超像素的闭环检测方法和Bag of Words方案。提出了一种新的超像素图像描述方法。我们的方法还利用了动态岛屿的概念,这使我们能够及时地对图像进行分组,并避免从同一地点拍摄的图像作为循环闭合候选图像在它们之间竞争。采用多个户外公共图像序列验证了所提出的方法,并与其他最先进的解决方案进行了比较。