Robust Relocalization and Its Evaluation for Online Environment Map Construction

The acquisition of surround-view panoramas using a single hand-held or head-worn camera relies on robust real-time camera orientation tracking and relocalization. This paper presents robust methodology and evaluation for camera orientation relocalization, using virtual keyframes for online environme...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 17(2011), 7 vom: 02. Juli, Seite 875-87
1. Verfasser: Kim, Sehwan (VerfasserIn)
Weitere Verfasser: Coffin, Christopher, Höllerer, Tobias
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2011
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.
Beschreibung
Zusammenfassung:The acquisition of surround-view panoramas using a single hand-held or head-worn camera relies on robust real-time camera orientation tracking and relocalization. This paper presents robust methodology and evaluation for camera orientation relocalization, using virtual keyframes for online environment map construction. In the case of tracking loss, incoming camera frames are matched against known-orientation keyframes to re-estimate camera orientation. Instead of solely using real keyframes from incoming video, the proposed approach employs virtual keyframes which are distributed strategically within completed portions of an environment map. To improve tracking speed, we introduce a new variant of our system which carries out relocalization only when tracking fails and uses inexpensive image-patch descriptors. We compare different system variants using three evaluation methods to show that the proposed system is useful in a practical sense. To improve relocalization robustness against lighting changes in indoor and outdoor environments, we propose a new approach based on illumination normalization and saturated area removal. We examine the performance of our solution over several indoor and outdoor video sequences, evaluating relocalization rates based on ground truth from a pan-tilt unit
Beschreibung:Date Completed 03.06.2016
Date Revised 05.02.2016
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
ISSN:1941-0506
DOI:10.1109/TVCG.2010.243