SYSTEM AND METHOD OF ANALYZING IMAGES USING A HIERARCHICAL SET OF MODELS

Number: 20170300781
Published: 2017-10-19
Filed: 2016-09-22
Assignee: DISNEY ENTERPRISES, INC.
Inventors: Lehrmann; Andreas et al.
CPC: G06V30/196; G06F18/28; G06V10/772; G06F18/231; G06V10/768; G06F18/24; G06V10/7625; G06F18/21
Verdict: Set aside hierarchical image classification models - generic content ML
Source: Google Patents · FreePatentsOnline

Abstract

One or more image parameters of an image may be analyzed using a hierarchical set of models. Executing individual models in the set of models may generate outputs from analysis of different image parameters of the image. Inputs of one or more of the models may be conditioned on a set of outputs derived from one or more preceding model in the hierarchy.

Background

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system configured for analyzing images using a hierarchical setof models, in accordance with one or more implementations.

FIG. 2 illustrates an exemplary visual representation of a hierarchical set of models used for analyzing images.

FIG. 3 illustrates an exemplary user interface, in accordance with one or more implementations.

FIG. 4 illustrates a method of analyzing images using a hierarchical set of models, in accordance with one or more implementations.DETAILED DESCRIPTION

FIG. 1 illustrates a system 100 configured for analyzing images using a hierarchical set of models, in accordance with one or more implementations. The hierarchical set of models may beconfigured such that individual models may be selectively executed without execution of the entire set of models. One or more of the models may be conditioned on a set of outputs derived from one or more preceding models such that output from an individual model may only require execution of a limited set of the models.

In some implementations, system100 may comprise a server 102, one or more computing platforms 118, and/or other components. The server 102 may include one or more physical processors 104 configured by machine-readable instructions 106. Executing the machine-readable instructions 106 may cause the one or more physical processors 104 to facilitate analyzing images using the hierarchical set of models. The machine-r

Claims

1. A system configured foranalyzing images using a hierarchical set of models, the system comprising: one or more physical processors configured by machine-readable instructions to: analyze an image by executing individual models in the hierarchical set of models, wherein executing the individual models in the set of models generates outputs from analysis of different image parameters of the image, wherein inputs of one or more of the models are solely conditioned on a complete set of outputs derived from a preceding model, the set of models includes: a firstmodel configured to generate outputs from analysis of a first image parameter; a second model configured to generate outputs from analysis of a second image parameter, the execution of the second model being conditioned on outputs of the first model; a third model configured to generate outputs from analysis of a third image parameter, execution of the third model being conditioned on outputs of the second model; wherein the generation of outputs by the first model is independent from any outputs of the second model and third model; and wherein the generation of outputs by the second model is conditioned on outputs of thefirst model and is independent from outputs of the third model. 12. A method of analyzingimages using a hierarchical set of models, the method being implemented in a computer system comprising one or more physical processors and storage media storing machine-readable instructions, the method comprising: analyzing an image by executing individual models in the hierarchical set of models, wherein executing the individual models in the set of models generates outputs from analysis of different image parameters of the image, wherein inputs of one or more of the models are solely conditioned on a complete set of outputs derived from a preceding model, the set of models includes: a first model configured to generate outputs from analysis of a first image parameter; a second model configured to generate outputs from analysis of a second image parameter, the execution of the second model beingconditioned on outputs of the first model; and a third model configured to generate outputs from analysis of a third image parameter, execution of the third model being conditioned on outputs of the second model; wherein the generation of outputs by the first model is independent from any outputs of the second model and third model; and wherein the generation of outputs by the second model is conditioned on outputs of the first model and is independent from outputs of the third model.