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A visual-inertial approach for camera egomotion estimation and simultaneous recovery of scene structure

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2 Author(s)
Dominik Aufderheide ; Intitute for Computer Science, -Vision and Computational Intelligence (CV&CI), South Westphalia University of Applied Sciences, Soest, Germany ; Werner Krybus

The estimation of a camera's egomotion is a highly desireable goal in many different application fields such as augmented reality (AR), visual navigation, robotics or entertainment. Especially for real-time modeling the former estimation of the camera trajectory is an elementary step towards the generation of three dimensional scene models. This paper presents a framework for simultaneous recovery of scene structure and camera motion by combining visual and inertial cues. For this purpose two different system designs are proposed: a loosely-coupled system and a monolithic design, which adapts ideas from non-linear state estimation as extended Kalman filtering (EKF) for structure and motion recovery.

Published in:

2010 IEEE International Conference on Virtual Environments, Human-Computer Interfaces and Measurement Systems

Date of Conference:

6-8 Sept. 2010