Geometry-Based Symbolic Approximation for Fast Sequence Matching on Manifolds

Author:

Anirudh Rushil,Turaga Pavan

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Reference55 articles.

1. Absil, P.-A., Mahony, R., & Sepulchre, R. (2004). Riemannian geometry of Grassmann manifolds with a view on algorithmic computation. Acta Applicandae Mathematicae, 80(2), 199–220.

2. Ali, S., Basharat, A., & Shah, M. (2007). Chaotic invariants for human action recognition. In ICCV (pp. 1–8).

3. Allauzen, C., & Raffinot, M. (2000). Simple optimal string matching algorithm. In Combinatorial Pattern Matching (Vol. 1848, pp. 364–374). Lecture Notes in Computer Science Berlin Heidelberg: Springer.

4. Boothby, W. M. (2003). An introduction to differentiable manifolds and Riemannian geometry (2nd ed.). New York: Academic Press.

5. Çetingül, H. E., & Vidal, R. (2009). Intrinsic mean shift for clustering on stiefel and grassmann manifolds. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 1896–1902). Miami.

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