Title: Parallel Tracking and Mapping for Small AR Workspaces
Abstract: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 ...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.Read More
Publication Year: 2007
Publication Date: 2007-11-01
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 3998
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot