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Bags of Binary Words for Fast Place Recognition in Image Sequences
TLDR
A vocabulary tree is built that discretizes a binary descriptor space and uses the tree to speed up correspondences for geometrical verification, and presents competitive results with no false positives in very different datasets.
Real-time loop detection with bags of binary words
TLDR
A method for detecting revisited places in a image sequence in real time by using efficient features and a direct index to take advantage of the bag of words to obtain correspondence points between two images efficiently, avoiding a matching of complexity Θ(n2).
RoboEarth - A World Wide Web for Robots
Towards semantic SLAM using a monocular camera
TLDR
This paper proposes a semantic SLAM algorithm that merges in the estimated map traditional meaningless points with known objects and builds a non-annotated map using only the information extracted from a monocular image sequence.
RoboEarth Semantic Mapping: A Cloud Enabled Knowledge-Based Approach
TLDR
This work describes the RoboEarth semantic mapping system and shows the synergetic relation of the SLAM map of objects that grounds the terminological knowledge coded in the ontology.
Robust place recognition with stereo cameras
TLDR
This paper presents an alternative system that makes use of stereo vision and combines two complementary techniques: bag-of-words to detect loop closing candidate images, and conditional random fields to discard those which are not geometrically consistent.
Hybrid laser and vision based object search and localization
TLDR
A method for an autonomous robot to efficiently locate one or more distinct objects in a realistic environment using monocular vision using receptive field cooccurrence histograms is described and results are presented showing its practicability and the quality of the position estimates obtained.
Robust Place Recognition With Stereo Sequences
TLDR
A place recognition algorithm for simultaneous localization and mapping systems using stereo cameras that considers both appearance and geometric information of points of interest in the images and carries out inference on a minimum spanning tree (MST), instead of a densely connected graph.
MOARSLAM: Multiple Operator Augmented RSLAM
TLDR
This paper presents a system which allows multiple clients to share and merge maps built from a state-of-the-art relative SLAM system, along with the server architecture and novel integrated multi-session loop closure system.
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