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|Title:||Automatic positioning data correction for sensor-annotated mobile videos||Authors:||Wang, G.
|Issue Date:||2012||Citation:||Wang, G.,Seo, B.,Zimmermann, R. (2012). Automatic positioning data correction for sensor-annotated mobile videos. GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems : 470-473. ScholarBank@NUS Repository. https://doi.org/10.1145/2424321.2424392||Abstract:||Video associated positioning data has become a useful contextual feature to facilitate analysis and management of media assets in GIS and social media applications. Moreover, with today's sensor-equipped mobile devices, the location of a camera can be continuously acquired in conjunction with the captured video stream without much difficulty. However, most sensor information collected from mobile devices is not highly accurate due to two main reasons: (a) the varying surrounding environmental conditions during data acquisition, and (b) the use of low-cost, consumer-grade sensors in current mobile devices. In this paper, we enhance the noisy positioning data generated by smartphones during video recording by analyzing typical error patterns for real collected data and introducing two robust algorithms, based on Kalman filtering and weighted linear least square regression, respectively. Our experimental results demonstrate significant benefits of our methods, which help upstream sensor-aided applications to access media content precisely. © 2012 Authors.||Source Title:||GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems||URI:||http://scholarbank.nus.edu.sg/handle/10635/42924||ISBN:||9781450316910||DOI:||10.1145/2424321.2424392|
|Appears in Collections:||Staff Publications|
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