In this paper, we propose an efficient algorithm for robust place recognition and loop detection using camera information only. Our pipeline purely relies on spatial localization and semantic information of road markings. The creation of the database of road markings sequences is performed online, which makes the method applicable for real-time loop closure for visual SLAM techniques. Furthermo...

Loop Closure Detection (LCD) has been proved to be extremely useful in global consistent visual Simultaneously Localization and Mapping (SLAM) and appearance-based robot relocalization. Methods exploiting binary features in bag of words representation have recently gained a lot of popularity for their efficiency, but suffer from low recall due to the inherent drawback that high dimensional bina...

Loop-closure detection on 3D data is a challenging task that has been commonly approached by adapting imagebased solutions. Methods based on local features suffer from ambiguity and from robustness to environment changes while methods based on global features are viewpoint dependent. We propose SegMatch, a reliable loop-closure detection algorithm based on the matching of 3D segments. Segments ...

With the development of related applications, indoor positioning techniques have been more and more widely developed. Based on Wi-Fi, Bluetooth low energy (BLE) and geomagnetism, indoor positioning techniques often rely on the physical location of fingerprint information. The focus and difficulty of establishing the fingerprint database are in obtaining a relatively accurate physical location w...

This paper proposes a novel visual loop-closure method using average feature descriptors. The average feature descriptors are computed by averaging the descriptors of feature points at each frame. Through GPGPU (General-Purpose computing on Graphics Processing Units) technique, the proposed method selects a frame having a minimum distance with the current average feature descriptor from the ave...

Loop closure detection for visual only simultaneous localization and mapping needs effective feature descriptors to obtain good performance results. Currently, the most widely used feature description is the global or local descriptor such as color histogram and Speeded Up Robust Features. The global features can be computed either by considering all points within a region, or only for those po...