AffTrack: robust tracking of features in variable-zoom videos

Authors:
Rodrigo Minetto;Neucimar J. Leite;Jorge Stolfi
Affiliations:
Institute of Computing, University of Campinas, Campinas, SP, Brazil;Institute of Computing, University of Campinas, Campinas, SP, Brazil;Institute of Computing, University of Campinas, Campinas, SP, Brazil
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 3
Cited 0

Stable Real-Time 3D Tracking Using Online and Offline Information

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Developing AR Applications with ARToolKit

ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
Monocular model-based 3D tracking of rigid objects

Foundations and Trends® in Computer Graphics and Vision

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Abstract

We describe a robust and accurate algorithm, nicknamed AffTrack, to track selected features of a rigid 3D object in a video recording, given a canonical image of each feature and its position on the object. AffTrack uses a synergistic combination of a multiscale feature finder and a flexible camera calibrator. This synergy between the two modules allows, AffTrack to recover features after occlusions of arbitrary duration. Compared to other solutions to this problem, AffTrack can handle videos with variable zoom, and variable lens distortion, does not require a complete geometric model of the object, and does not require the selection of key frames. Tests indicate that AffTrack is more robust and accurate than the popular object trackers include in H. Kato's ARToolKit and in the OpenCV library.