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Augmented Reality System for Accelerometer Equipped Mobile Devices

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2 Author(s)
Skoczewski, M. ; Grad. Sch. of Sci. & Eng., Saitama Univ., Saitama, Japan ; Maekawa, H.

In this paper, we present a novel approach for mobile augmented reality system. We estimate the 3D camera pose by detecting local invariant image features and combining them with the camera's accelerometer data. We applied NELFD - Neuroevolved Local Feature Descriptor that encodes data around points of interest in the image using a neural network with evolved topology and weights. For every image frame, a correspondence between 2D feature points is calculated and the camera's pose is established based on additional sensor information. Generally mobile systems are low performance and equipped with low-grade camera. Thus, due to estimation accuracy and low computational complexity our approach has been considered as a new alternative in the mobile augmenting process. Experimental evaluation proved that our method is capable of real-time pose tracking and augmentation in an unconstrained environment.

Published in:

Computer and Information Science (ICIS), 2010 IEEE/ACIS 9th International Conference on

Date of Conference:

18-20 Aug. 2010