US 2020/0349189 A1 · Compositing Aware Digital Image Search

Abstract

Compositing aware digital image search techniques and systems are described that leverage machine learning. In one example, a compositing aware image search system employs a two-stream convolutional neural network (CNN) to jointly learn feature embeddings from foreground digital images that capture a foreground object and background digital images that capture a background scene. In order to train models of the convolutional neural networks, triplets of training digital images are used. Each triplet may include a positive foreground digital image and a positive background digital image taken from the same digital image. The triplet also contains a negative foreground or background digital image that is dissimilar to the positive foreground or background digital image that is also included as part of the triplet.

Claims20

Dependent claims

In a digital medium compositing aware digital image search environment, a method implemented by at least one computing device, the method comprising:

receiving, by the at least one computing device, foreground features extracted from a foreground of a digital image using machine learning;
searching, by the at least one computing device, a plurality of candidate digital images based on:
background features extracted from backgrounds of the plurality of candidate digital images, respectively, using machine learning;
and
the foreground features from the foreground of the digital image;
generating, by the at least one computing device, a search result including at least one of the plurality of candidate digital images based on the searching;
and
outputting, by the at least one computing device, the search result.

5 more elements

Dependencies are inferred from the claim text.

Compositing Aware Digital Image Search

Life of this patent

Compositing Aware Digital Image Search

Life of this patent

Abstract

Claims20