Accelerometer Localization in the View of a Stationary Camera

Stein, S. and McKenna, S. J. (2012) Accelerometer Localization in the View of a Stationary Camera. In: 2012 Ninth Conference on Computer and Robot Vision (CRV), Toronto, ON, Canada, 28-30 May 2012, pp. 109-116. ISBN 9781467312714 (doi: 10.1109/CRV.2012.22)

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This paper addresses the problem of localizing an accelerometer in the view of a stationary camera as a first step towards multi-model activity recognition. This problem is challenging as accelerometers are visually occluded, they measure proper acceleration including effects of gravity and their orientation is unknown and changes over time relative to camera viewpoint. Accelerometers are localized by matching acceleration estimated along visual point trajectories to accelerometer data. Trajectories are constructed from point feature tracking (KLT) and by grid sampling from a dense flow field. We also construct 3D trajectories with visual depth information. The similarity between accelerometer data and a trajectory is computed by counting the number of frames in which the norms of accelerations in both sequences exceed a threshold. For quantitative evaluation we collected a challenging dataset consisting of video and accelerometer data of a person preparing a mixed salad with accelerometer-equipped kitchen utensils. Trajectories from dense optical flow yielded a higher localization accuracy compared to point feature tracking.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Stein, Dr Sebastian
Authors: Stein, S., and McKenna, S. J.
College/School:College of Science and Engineering > School of Computing Science

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