A Fast and Incremental Method for Loop-Closure Detection Using Bags of Visual Words
نویسندگان
چکیده
In robotic applications of visual simultaneous localization and mapping techniques, loop-closure detection and global localization are two issues that require the capacity to recognize a previously visited place from current camera measurements. We present an online method that makes it possible to detect when an image comes from an already perceived scene using local shape and color information. Our approach extends the bag-of-words method used in image classification to incremental conditions and relies on Bayesian filtering to estimate loop-closure probability. We demonstrate the efficiency of our solution by real-time loop-closure detection under strong perceptual aliasing conditions in both indoor and outdoor image sequences taken with a handheld camera.
منابع مشابه
iBoW-LCD: An Appearance-based Loop Closure Detection Approach using Incremental Bags of Binary Words
In this paper, we introduce iBoW-LCD, a novel appearance-based loop closure detection method. The presented approach makes use of an incremental Bag-of-Words (BoW) scheme based on binary descriptors to retrieve previously seen similar images, avoiding any vocabulary training stage usually required by classic BoW models. In addition, to detect loop closures, iBoW-LCD builds on the concept of dyn...
متن کاملDétection visuelle de fermeture de boucle et applications à la localisation et cartographie simultanées. (Visual SLAM applications of loop-closure detection)
Title : Visual SLAM applications of loop-closure detection Loop-closure detection is crucial for enhancing the robustness of SLAM algorithms in general. For example, after a long travel in unknown terrain, detecting when the robot has returned to a past location makes it possible to increase the accuracy and the consistency of the estimation. Recognizing previously mapped locations can also be ...
متن کاملCombining Odometry and Visual Loop-Closure Detection for Consistent Topo-Metrical Mapping
We address the problem of simultaneous localization and mapping (SLAM) by combining visual loop-closure detection with metrical information given by a robot odometry. The proposed algorithm extends a purely appearance-based loopclosure detection method based on bags of visual words [1] which is able to detect when the robot has returned back to a previously visited place. An efficient optimizat...
متن کاملTree of Words for Visual Loop Closure Detection in Urban SLAM
This paper introduces vision based loop closure detection in Simultaneous Localisation And Mapping (SLAM) using Tree of Words. The loop closure performance in a complex urban environment is examined and an additional feature is suggested for safer matching. A SLAM ground experiment in an urban area is performed using Tree of Words, a delayed state information filter and planar laser scans for r...
متن کاملVisual Loop Closure Detection with Scene Mutual Information for Mobile Robot
In this paper, an efficient approach is proposed for loop-closure detection in robot visual SLAM. The method uses mutual information to measure similarity between current view and key frames in an appearance map, and evaluates candidate loop-closure locations in particle filter framework. Specially, the implementation of particle filter is accelerated through updating a set of weight vector of ...
متن کامل