Dropbox, Inc.
Semantic image retrieval

Abstract:

Computer-implemented techniques for sematic image retrieval are disclosed. Digital images are classified into N number of categories based on their visual content. The classification provides a set of N-dimensional image vectors for the digital images. Each image vector contains up to N number of probability values for up to N number of corresponding categories. An N-dimensional image match vector is generated that projects an input keyword query into the vector space of the set of image vectors by computing the vector similarities between a word vector for the input query and a word vector for each of the N number of categories. Vector similarities between the image match vectors and the set of image vectors can be computed to determine images semantically relevant to the input query.