Computer vision training using paired image data

Abstract

A method of training a computer vision to visually recognize and identify objects includes, in part, supplying N pairs of images to the computer with each pair including first and second images. The first image in each pair includes data representative of a scene as well as an object to be recognized. The second image of each pair includes only the data representative of the scence and thus does not include the object. The training method may further include minimizing a loss function represented by a sum, over all N images, of a conditional probability of finding the object in the i-th image and a conditional probability of not finding the object in the i-th image.

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