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Recognition and reconstruction of objects with partial appearance

  • US 10,460,470 B2
  • Filed: 07/06/2017
  • Issued: 10/29/2019
  • Est. Priority Date: 07/06/2017
  • Status: Active Grant
First Claim
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1. A system operable to recognize and reconstruct objects in images, the system comprising:

  • a non-transitory memory storage comprising instructions; and

    one or more processors in communication with the non-transitory memory storage, wherein the one or more processors execute the instructions to perform operations comprising;

    acquiring a plurality of images, each image including an object within the image, the object having a different appearance in a number of images of the plurality of images;

    decomposing, for each image, the object into components and generating label data for each image;

    inputting the images and associated label data into a learning module to train the learning module to recognize the components of the object, the training being based on an overall objectness score of the object, an objectness score of each component of the object, a pose of the object, and a pose of each component of the object for each image input;

    inputting an additional image into the trained learning module;

    detecting that the additional image has one or more of the components of the object within the additional image in response to input into the trained learning module; and

    identifying the object and estimating its pose information in the additional image and/or constructing a complete view of the object in the additional image or a complete sketch of the object in response to detection of the one or more of the components, wherein training the learning module includes minimizing a cost function generated as a sum of discrepancies between the label data and computed data for a set of items, the set of items including the overall objectness score, the objectness scores of the components, the pose of the object, and the poses of the components.

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