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ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
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CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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Recognizing human actions in video sequences is attracting much attention, and this paper aims to deal with the problem of action recognition with salient trajectories. First, two kinds of trajectory saliency values, appearance and motion saliency, are calculated and combined to capture complementary information. Secondly, the combined saliency is utilized to prune redundant trajectories, and a compact and discriminative set of trajectories is obtained. Finally, kernel histograms are applied for the description of salient trajectories and human actions are classified by the bag-of-words approach. The proposed approach is validated on three public datasets including KTH, ADL, and UCF. Experimental results show that the method achieves superior results on the KTH and ADL datasets and comparable results with other state-of-the-art methods on the UCF dataset.