scispace - formally typeset
Journal ArticleDOI

Navigating, Recognizing and Describing Urban Spaces With Vision and Lasers

Reads0
Chats0
TLDR
A body of work aimed at extending the reach of mobile navigation and mapping is described, showing how running topological and metric mapping and pose estimation processes concurrently, using vision and laser ranging, has produced a full six-degree-of-freedom outdoor navigation system.
Abstract
In this paper we describe a body of work aimed at extending the reach of mobile navigation and mapping. We describe how running topological and metric mapping and pose estimation processes concurrently, using vision and laser ranging, has produced a full six-degree-of-freedom outdoor navigation system. It is capable of producing intricate three-dimensional maps over many kilometers and in real time. We consider issues concerning the intrinsic quality of the built maps and describe our progress towards adding semantic labels to maps via scene de-construction and labeling. We show how our choices of representation, inference methods and use of both topological and metric techniques naturally allow us to fuse maps built from multiple sessions with no need for manual frame alignment or data association.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments

TL;DR: This paper presents RGB-D Mapping, a full 3D mapping system that utilizes a novel joint optimization algorithm combining visual features and shape-based alignment to achieve globally consistent maps.
Book ChapterDOI

RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments

TL;DR: This paper presents RGB-D Mapping, a full 3D mapping system that utilizes a novel joint optimization algorithm combining visual features and shape-based alignment to achieve globally consistent maps.
Journal ArticleDOI

Visual Place Recognition: A Survey

TL;DR: A survey of the visual place recognition research landscape is presented, introducing the concepts behind place recognition, how a “place” is defined in a robotics context, and the major components of a place recognition system.
Book ChapterDOI

Visual Odometry and Mapping for Autonomous Flight Using an RGB-D Camera

TL;DR: A system for visual odometry and mapping using an RGB-D camera, and its application to autonomous flight, which enables 3D flight in cluttered environments using only onboard sensor data.
Journal ArticleDOI

Appearance-only SLAM at large scale with FAB-MAP 2.0

TL;DR: A new formulation of appearance-only SLAM suitable for very large scale place recognition that incorporates robustness against perceptual aliasing and substantially outperforms the standard term-frequency inverse-document-frequency (tf-idf) ranking measure.
References
More filters
Journal ArticleDOI

Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

TL;DR: New results are derived on the minimum number of landmarks needed to obtain a solution, and algorithms are presented for computing these minimum-landmark solutions in closed form that provide the basis for an automatic system that can solve the Location Determination Problem under difficult viewing.
Journal ArticleDOI

A method for registration of 3-D shapes

TL;DR: In this paper, the authors describe a general-purpose representation-independent method for the accurate and computationally efficient registration of 3D shapes including free-form curves and surfaces, based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a geometric entity to a given point.
Journal ArticleDOI

A Tutorial on Support Vector Machines for Pattern Recognition

TL;DR: There are several arguments which support the observed high accuracy of SVMs, which are reviewed and numerous examples and proofs of most of the key theorems are given.
Book

Multiple view geometry in computer vision

TL;DR: In this article, the authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly in a unified framework, including geometric principles and how to represent objects algebraically so they can be computed and applied.

Multiple View Geometry in Computer Vision.

TL;DR: This book is referred to read because it is an inspiring book to give you more chance to get experiences and also thoughts and it will show the best book collections and completed collections.
Related Papers (5)