Title :
AffTrack: Robust tracking of features in variable-zoom videos
Author :
Minetto, Rodrigo ; Leite, Neucimar J. ; Stolfi, Jorge
Author_Institution :
Inst. of Comput., Univ. of Campinas, Campinas, Brazil
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.
Keywords :
calibration; cameras; feature extraction; video recording; video signal processing; AffTrack algorithm; feature tracking; flexible camera calibrator; multiscale feature finder; occlusions; rigid 3D object; variable lens distortion; variable zoom; video recording; Augmented reality; Calibration; Cameras; Lenses; Libraries; Robustness; Shape; Solid modeling; Testing; Video recording; Camera calibration; augmented reality; feature tracking; object tracking;
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2009.5413694