In this work, we address the problem of analyzing video sequences by representing meaningful local spaceâtime 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 spaceâtime 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 spaceâtime primitives for a video sequence in an unsupervised way.
|Titolo:||Space-Time Signal Analysis and the 3D Shearlet Transform|
|Data di pubblicazione:||2018|
|Appare nelle tipologie:||01.01 - Articolo su rivista|
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