Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICME.2010.5583850
Title: Model-based localization and drift-free user tracking for outdoor augmented reality
Authors: Karlekar, J. 
Zhou, S.Z.Y. 
Nakayama, Y. 
Lu, W. 
Chang Loh, Z.
Hii, D. 
Keywords: Drift-free camera tracking
Mobile augmented reality
Shape matching
User localization
Issue Date: 2010
Citation: Karlekar, J., Zhou, S.Z.Y., Nakayama, Y., Lu, W., Chang Loh, Z., Hii, D. (2010). Model-based localization and drift-free user tracking for outdoor augmented reality. 2010 IEEE International Conference on Multimedia and Expo, ICME 2010 : 1178-1183. ScholarBank@NUS Repository. https://doi.org/10.1109/ICME.2010.5583850
Abstract: In this paper we present a novel model-based hybrid technique for user localization and drift-free tracking in urban environments. In outdoor augmented reality, instantaneous 6-DoF user localization is achieved with position and orientation sensors such as GPS and gyroscopes. Initial pose obtained with these sensors is dominated by large positional errors due to coarse granularity of GPS data. Subsequent tracking is also erroneous as gyroscopes are prone to drifts and often need recalibration. We propose to use model-to-image registration technique to refine initial rough estimate for accurate user localization. Large positional errors in user localization are mitigated by aligning silhouettes of the model with that of the camera image using shape context descriptors as they are invariant to translation, scale and rotational errors. Once initialized, drift-free tracking is achieved by combining frame-to-frame and model-to-frame feature tracking. Frame-to-frame tracking is done by matching corners whereas edges are used for model-to-frame silhouette tracking. Final camera pose is obtained with M-estimators. © 2010 IEEE.
Source Title: 2010 IEEE International Conference on Multimedia and Expo, ICME 2010
URI: http://scholarbank.nus.edu.sg/handle/10635/46323
ISBN: 9781424474912
DOI: 10.1109/ICME.2010.5583850
Appears in Collections:Staff Publications

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