Abstract
An effective framework for dynamic texture recognition is introduced by exploiting local features and chaotic motions along beams of dense trajectories in which their motion points are encoded by using a new operator, named \(\mathrm {LVP}_{full}\text {-TOP}\), based on local vector patterns (LVP) in full-direction on three orthogonal planes. Furthermore, we also exploit motion information from dense trajectories to boost the discriminative power of the proposed descriptor. Experiments on various benchmarks validate the interest of our approach.
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Notes
- 1.
http://lear.inrialpes.fr/people/wang/dense_trajectories.
- 2.
Please see [26] for more details about these above parameters.
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Nguyen, T.T., Nguyen, T.P., Bouchara, F., Nguyen, X.S. (2018). Directional Beams of Dense Trajectories for Dynamic Texture Recognition. In: Blanc-Talon, J., Helbert, D., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2018. Lecture Notes in Computer Science(), vol 11182. Springer, Cham. https://doi.org/10.1007/978-3-030-01449-0_7
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