Paper Info
Title
Live tracking and mapping from both general and rotation-only camera motion
Abstract
We present an approach to real-time tracking and mapping that supports any type of camera motion in 3D environments, that is, general (parallax-inducing) as well as rotation-only (degenerate) motions. Our approach effectively generalizes both a panorama mapping and tracking system and a keyframe-based Simultaneous Localization and Mapping (SLAM) system, behaving like one or the other depending on the camera movement. It seamlessly switches between the two and is thus able to track and map through arbitrary sequences of general and rotation-only camera movements. Key elements of our approach are to design each system component such that it is compatible with both panoramic data and Structure-from-Motion data, and the use of the `Geometric Robust Information Criterion' to decide whether the transformation between a given pair of frames can best be modeled with an essential matrix E, or with a homography H. Further key features are that no separate initialization step is needed, that the reconstruction is unbiased, and that the system continues to collect and map data after tracking failure, thus creating separate tracks which are later merged if they overlap. The latter is in contrast to most existing tracking and mapping systems, which suspend tracking and mapping, thus discarding valuable data, while trying to relocalize the camera with respect to the initial map. We tested our system on a variety of video sequences, successfully tracking through different camera motions and fully automatically building panoramas as well as 3D structures.
Year
DOI
Venue
2012
10.1109/ISMAR.2012.6402532
Mixed and Augmented Reality
Keywords
Field
DocType
rotation-only camera motion,panorama mapping,camera movement,arbitrary sequence,real-time tracking,camera motion,live tracking,keyframe-based simultaneous localization,rotation-only camera movement,real time systems,merging,robustness,data models,tracking,simultaneous localization and mapping
Data modeling,Computer vision,Computer graphics (images),Panorama,Computer science,Tracking system,Robustness (computer science),Artificial intelligence,Simultaneous localization and mapping,Merge (version control)
Conference
ISSN
ISBN
Citations 
1554-7868
978-1-4673-4661-0
18
PageRank 
References 
Authors
0.74
32
5
Name
Order
Citations
PageRank
Steffen Gauglitz136014.32
Chris Sweeney21017.42
Jonathan Ventura322420.60
Matthew Turk43724499.42
Tobias Höllerer52666244.50