Systems and Methods for Identifying Activities in Media Contents Based on Prediction Confidences

Number: 20170308756
Published: 2017-10-26
Filed: 2016-07-14
Assignee: DISNEY ENTERPRISES, INC.
Inventors: Sigal; Leonid et al.
CPC: G06N3/0442; G06N3/0464; G06N3/09; G06T7/62; G06T7/90; G06V10/454; G06V20/20; G06V20/41; G06V20/46; G06V20/47; G06V40/20; G11B27/102; H04L65/61
Verdict: Set aside media content activity ID via prediction confidence - content analytics
Source: Google Patents · FreePatentsOnline

Abstract

There is provided a system comprising a memory and a processor configured to receive a media content depicting an activity, extract a first plurality of features from a first segment of the media content, make a first prediction that the media content depicts a first activity based on the first plurality of features, wherein the first prediction has a first confidence level, extract a second plurality of features from a second segment of the media content, the second segment temporally following the first segment in the media content, make a second prediction that the media content depicts the first activity based on the second plurality of features, wherein the second prediction has a second confidence level, determine that the media content depicts the first activity based on the first prediction and the second prediction, wherein the second confidence level is at least as high as the first confidence level.

Background

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a diagram of an exemplary system for identifying activities in a media content based on prediction confidences, according to one implementation of the present disclosure;

FIG. 2 shows a diagram of frames from an exemplary media content and associated predictions, according to one implementation of the present disclosure;

FIG. 3 shows a diagram of an exemplary sequence of identifying an activity using the system of FIG. 1, according to one implementation of the present disclosure;

FIG. 4 shows a diagram of exemplary activities identified using the system of FIG. 1, according to one implementation of the present disclosure;

FIG. 5 shows a flowchart illustrating an exemplary method of training the system of FIG. 1 for identifying activities in media content based on prediction confidences, according to one implementation of the present disclosure; and

FIG. 6 shows a flowchart illustrating an exemplary method of identifying activities in a media content based on prediction confidences, according to one implementation of the present disclosure.DETAILED DESCRIPTION

The following description contains specific information pertaining to implementations in the present disclosure. The drawings in the present application and their accompanying detailed description are directed to merely exemplary implementations. Unless noted otherwise, like or corresponding elements among the figures may be indicate

Claims

1. A system comprising: a non-transitory memory storing an executable code and an activity database; and a hardware processor executing the executable code to: receive a media content including a plurality of segments depicting an activity; extracta first plurality of features from a first segment of the plurality of segments; make a first prediction that the media content depicts a first activity from the activity databasebased on the first plurality of features, wherein the first prediction has a first confidence level; extract a second plurality of features from a second segment of the plurality of segments, the second segment temporally following the first segment in the media content; make a second prediction that the media content depicts the first activity based on thesecond plurality of features, wherein the second prediction has a second confidence level; and determine that the media content depicts the first activity based on the first prediction and the second prediction, wherein the second confidence level is at least as high as the first confidence level. 11. A method for use with a system including a non-transitory memory and a hardware processor, the method comprising: receiving, using the hardware processor, a media content including a plurality of segments depicting an activity; extracting, using the hardware processor, a first plurality of features from a first segment of the plurality of segments; making, using the hardware processor, a first prediction that themedia content depicts a first activity from the activity database based on the first plurality of features, wherein the first prediction has a first confidence level; extracting, using the hardware processor, a second plurality of features from a second segment of the plurality of segments, the second segment temporally following the first segment in the media content; making, using the hardware processor, a second prediction that the media content depicts the first activity based on the second plurality of features, wherein the second prediction has a second confidence level; and determining, using the hardware processor, that the media content depicts the first activity based on the first prediction and the second prediction, wherein the second confidence level is at least as high as the first confidence level.