Title :
Scene modelling, recognition and tracking with invariant image features
Author :
Skrypnyk, Iryna ; Lowe, David G.
Author_Institution :
Dept. of Comput. Sci., British Columbia Univ., Vancouver, BC, Canada
Abstract :
We present a complete system architecture for fully automated markerless augmented reality (AR). The system constructs a sparse metric model of the real-world environment, provides interactive means for specifying the pose of a virtual object, and performs model-based camera tracking with visually pleasing augmentation results. Our approach does not require camera pre-calibration, prior knowledge of scene geometry, manual initialization of the tracker or placement of special markers. Robust tracking in the presence of occlusions and scene changes is achieved by using highly distinctive natural features to establish image correspondences.
Keywords :
augmented reality; cameras; image recognition; optical tracking; solid modelling; automated markerless augmented reality; image correspondences; invariant image features; model-based camera tracking; natural features; occlusions; real-world environment; robust tracking; scene changes; scene modelling; scene recognition; scene tracking; sparse metric model; system architecture; virtual object; Augmented reality; Calibration; Cameras; Computer architecture; Computer science; Geometry; Image recognition; Layout; Power system modeling; Robustness;
Conference_Titel :
Mixed and Augmented Reality, 2004. ISMAR 2004. Third IEEE and ACM International Symposium on
Print_ISBN :
0-7695-2191-6
DOI :
10.1109/ISMAR.2004.53