作者: Andrei State , Gentaro Hirota , David T. Chen , William F. Garrett , Mark A. Livingston
关键词: Landmark 、 Artificial intelligence 、 Robustness (computer science) 、 Computer science 、 Computer vision 、 Augmented reality 、 Magnetic tracking 、 Video tracking 、 Usability
摘要: Accurate registration between real and virtual objects is crucial for augmented reality applications. Existing tracking methods are individually inadequate: magnetic trackers inaccurate, mechanical cumbersome, vision-based computationally problematic. We present a hybrid method that combines the accuracy of with robustness without compromising real-time performance or usability. demonstrate excellent in three sample CR