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Parallel Tracking and Mapping for Small AR Workspaces


This paper presents a method of estimating camera pose in an unknown
scene. While this has previously been attempted by adapting
SLAM algorithms developed for robotic exploration, we propose a
system specifically designed to track a hand-held camera in a small
AR workspace. We propose to split tracking and mapping into two
separate tasks, processed in parallel threads on a dual-core computer:
one thread deals with the task of robustly tracking erratic
hand-held motion, while the other produces a 3D map of point features
from previously observed video frames. This allows the use of
computationally expensive batch optimisation techniques not usually
associated with real-time operation: The result is a system that
produces detailed maps with thousands of landmarks which can be
tracked at frame-rate, with an accuracy and robustness rivalling that
of state-of-the-art model-based systems.



3D空間の認識が難しいマーカーレスなARシステムにおいて現実3D空間上で特徴点を利用しそれをトラッキング(追跡)すると同時にマッピングも(parallel threadsにおいて)行うことで、精度とロバスト性とスピードをあげること。

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