Yael Yankelevsky

We don’t have enough information about this author to calculate their statistics. If you think this is an error let us know.
Learn More
In this paper, we propose a supervised dictionary learning algorithm that aims to preserve the local geometry in both dimensions of the data. A graph-based regularization explicitly takes into account the local manifold structure of the data points. A second graph regularization gives similar treatment to the feature domain and helps in learning a more(More)
An autostereogram is a single image that encodes depth information that pops out when looking at it. The trick is achieved by setting a basic 2D pattern and continuously replicating the local pattern at each point in the image with a shift defined by the desired disparity. In this work, we explore the dependency between the ease of perceiving depth in(More)
Given N points in the plane P1, P2, ..., PN and a location Ω, the union of discs with diameters [ΩPi], i = 1, 2, ..., N covers the convex hull of the points. The location Ωs minimizing the area covered by the union of discs, is shown to be the Steiner center of the convex hull of the points. Similar results for d-dimensional Euclidean space are conjectured.
  • 1