Patents by Inventor Scott Daniel Helmer

Scott Daniel Helmer 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).

  • Patent number: 10438262
    Abstract: A virtual browsing experience may be implemented that allows a user to move a mobile device within a physical environment in order to control browser navigation to different items on an associated display. The virtual browsing experience improves the user's ability to recall where previously-viewed items are located in the virtual browsing environment. In some embodiments, a mobile device may determine its position and/or orientation in a physical environment, and when movement of the mobile device is detected, a user interface on an associated display may digitally navigate through multiple items according to the position and/or orientation of the mobile device. The position and orientation of the mobile device may be determined from position information or data obtained by a sensor device of the mobile device, and appropriate subsets of items can be determined for display based on detected movement of the mobile device.
    Type: Grant
    Filed: June 15, 2015
    Date of Patent: October 8, 2019
    Assignee: Amazon Technologies, Inc.
    Inventors: Scott Daniel Helmer, Junxiong Jia
  • Patent number: 10380461
    Abstract: Approaches introduce a pre-processing and post-processing framework to a neural network-based approach to identify items represented in an image. For example, a classifier that is trained on several categories can be provided. An image that includes a representation of an item of interest is obtained. Rotated versions of the image are generated and each of a subset of the rotated images is analyzed to determine a probability that a respective image includes an instance of a particular category. The probabilities can be used to determine a probability distribution of output category data, and the data can be analyzed to select an image of the rotated versions of the image. Thereafter, a categorization tree can then be utilized, whereby for the item of interest represented the image, the category of the item can be determined. The determined category can be provided to an item retrieval algorithm to determine primary content for the item of interest.
    Type: Grant
    Filed: October 20, 2017
    Date of Patent: August 13, 2019
    Assignee: A9.COM, INC.
    Inventors: Avinash Aghoram Ravichandran, Matias Omar Gregorio Benitez, Rahul Bhotika, Scott Daniel Helmer, Anshul Kumar Jain, Junxiong Jia, Rakesh Madhavan Nambiar, Oleg Rybakov
  • Patent number: 9830534
    Abstract: Approaches introduce a pre-processing and post-processing framework to a neural network-based approach to identify items represented in an image. For example, a classifier that is trained on several categories can be provided. An image that includes a representation of an item of interest is obtained. Rotated versions of the image are generated and each of a subset of the rotated images is analyzed to determine a probability that a respective image includes an instance of a particular category. The probabilities can be used to determine a probability distribution of output category data, and the data can be analyzed to select an image of the rotated versions of the image. Thereafter, a categorization tree can then be utilized, whereby for the item of interest represented the image, the category of the item can be determined. The determined category can be provided to an item retrieval algorithm to determine primary content for the item of interest.
    Type: Grant
    Filed: December 16, 2015
    Date of Patent: November 28, 2017
    Assignee: A9.com, Inc.
    Inventors: Avinash Aghoram Ravichandran, Matias Omar Gregorio Benitez, Rahul Bhotika, Scott Daniel Helmer, Anshul Kumar Jain, Junxiong Jia, Rakesh Madhavan Nambiar, Oleg Rybakov