Patents by Inventor Arial Shamir

Arial Shamir has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Content aware resizing of images and videos
    Patent number: 8380010
    Abstract: A method resizes input images by first constructing a grid graph. The grid graph includes one node for each pixel in the input image, and adjacent nodes in the grid graph are connected by arcs. Each arc is directed and has an associated cost. A cut is applied to the arcs of the grid graph using a cost function. A seam of pixels is determined from the cut so that coordinates of the pixels in the seam enforce monotonicity and connectivity constraints. Then, the input image is resized according to the seam to produce an output image while minimizing a change of energy in the output image when compared with the input image.
    Type: Grant
    Filed: November 12, 2008
    Date of Patent: February 19, 2013
    Assignee: Mitsubishi Electric Research Laboratories, Inc.
    Inventors: Michael Rubenstein, Arial Shamir, Shmuel Avidan, Matthew E. Brand
  • Content Aware Resizing of Images and Videos
    Publication number: 20110211771
    Abstract: A method resizes input images by first constructing a grid graph. The grid graph includes one node for each pixel in the input image, and adjacent nodes in the grid graph are connected by arcs. Each arc is directed and has an associated cost. A cut is applied to the arcs of the grid graph using a cost function. A seam of pixels is determined from the cut so that coordinates of the pixels in the seam enforce monotonicity and connectivity constraints. Then, the input image is resized according to the seam to produce an output image while minimizing a change of energy in the output image when compared with the input image.
    Type: Application
    Filed: November 12, 2008
    Publication date: September 1, 2011
    Inventors: Michael Rubenstein, Arial Shamir, Shmuel Avidan, Matthew E. Brand