Title :
A visual-inertial approach for camera egomotion estimation and simultaneous recovery of scene structure
Author :
Aufderheide, Dominik ; Krybus, Werner
Author_Institution :
Intitute for Comput. Sci., -Vision & Comput. Intell. (CV&CI), South Westphalia Univ. of Appl. Sci., Soest, Germany
Abstract :
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.
Keywords :
Kalman filters; motion estimation; state estimation; augmented reality; camera egomotion estimation; camera motion; camera trajectory; entertainment; extended Kalman filtering; former estimation; loosely-coupled system; monolithic design; motion recovery; nonlinear state estimation; real-time modeling; robotics; scene structure; three dimensional scene models; visual navigation; visual-inertial approach; Accelerometers; Cameras; Estimation; Feature extraction; Robot sensing systems; Robustness; Visualization; Computer Vision; Extended Kalman filtering; Interial Sensing; Scene Acquisition; Sensor Fusion; Stapdown algorithm; Structure from Motion (SfM);
Conference_Titel :
Virtual Environments Human-Computer Interfaces and Measurement Systems (VECIMS), 2010 IEEE International Conference on
Conference_Location :
Taranto
Print_ISBN :
978-1-4244-5904-9
DOI :
10.1109/VECIMS.2010.5609344
