This paper presents a novel technique for performing SLAM along a continuous trajectory of appearance. Derived from components of FastSLAM and FAB-MAP, the new system dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM) augments appearancebased place recognition with particle-filter based ‘pose filtering’ within a probabilistic framework, without calculating global feature geometry or ...

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 informatio...

Vision-based simultaneous localization and mapping (vSLAM) is a well-established problem in mobile robotics and monocular vSLAM is one of the most challenging variations of that problem nowadays. In this work we study one of the core post-processing optimization mechanisms in vSLAM, e.g. loop-closure detection. We analyze the existing methods and propose original algorithm for loop-closure dete...

conclusions the analytical sensitivity of lamp and pcr methods, using the designed primers, was 8 times more than any other reported methods. the designed methods are specific and sensitive for detection of h. pylori in different clinical and environmental samples. results the detection limits of the lamp and pcr assay were similar and were 10 fg of pure dna of h. pylori, which is equal to 6 co...

In this paper the problem of 3D scene and object classification from depth data is addressed. In contrast to high-dimensional feature-based representation, the depth data is described in a low dimensional space. In order to remedy the curse of dimensionality problem, the depth data is described by a sparse model over a learned dictionary. Exploiting the algorithmic information theory, a new def...

We present an approach for detecting loop closures in a large sequence of omni-directional images of urban environments. In particular we investigate the efficacy of global gist descriptors computed for 360 cylindrical panoramas and compare it with the baseline vocabulary tree approach. In the context of loop closure detection, we describe a novel matching strategy for panoramic views, exploiti...