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Ordered trajectories for large scale human action recognition

Murthy, O.V. Ramana; Goecke, Roland


Recently, a video representation based on dense trajectories has been shown to outperform other human action recognition methods on several benchmark datasets. In dense trajectories, points are sampled at uniform intervals in space and time and then tracked using a dense optical flow field. The uniform sampling does not discriminate objects of interest from the background or other objects. Consequently, a lot of information is accumulated, which actually may not be useful. Sometimes, this...[Show more]

CollectionsANU Research Publications
Date published: 2013
Type: Conference paper
Source: Proceedings of the IEEE International Conference on Computer Vision
DOI: 10.1109/ICCVW.2013.61


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