Space–Time Signal Analysis and the 3D Shearlet Transform
| Autor: | Francesca Odone, Ernesto De Vito, Damiano Malafronte |
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| Rok vydání: | 2018 |
| Předmět: |
Statistics and Probability
Root (linguistics) Computer science 02 engineering and technology 2D $$+~T$$+Tsignal analysis Shearlet transform Spaceâtime local primitives Modeling and Simulation Condensed Matter Physics 1707 Geometry and Topology Applied Mathematics 01 natural sciences 0202 electrical engineering electronic engineering information engineering 0101 mathematics Representation (mathematics) Signal processing Space time SIGNAL (programming language) Video sequence Spaceâ time local primitives 010101 applied mathematics 020201 artificial intelligence & image processing Gravitational singularity Computer Vision and Pattern Recognition Algorithm |
| Zdroj: | Journal of Mathematical Imaging and Vision. 60:1008-1024 |
| ISSN: | 1573-7683 0924-9907 |
| DOI: | 10.1007/s10851-018-0791-3 |
| Popis: | In this work, we address the problem of analyzing video sequences by representing meaningful local space–time neighborhoods. We propose a mathematical model to describe relevant points as local singularities of a 3D signal, and we show that these local patterns can be nicely highlighted by the 3D shearlet transform, which is at the root of our work. Based on this mathematical framework, we derive an algorithm to represent space–time points which is very effective in analyzing video sequences. In particular, we show how points of the same nature have a very similar representation, allowing us to compute different space–time primitives for a video sequence in an unsupervised way. |
| Databáze: | OpenAIRE |
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