Systems and methods for identifying activities and/or events in media contents based on object data and scene data

Number: 9940522
Published: 2018-04-10
Filed: 2016-07-15
Assignee: Disney Enterprises, Inc.
Inventors: Wu; Zuxuan 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/event identification, content indexing
Source: Google Patents · FreePatentsOnline

Abstract

There is provided a system including a non-transitory memory storing an executable code and a hardware processor executing the executable code to receive a plurality of training contents depicting a plurality of activities, extract training object data from the plurality of training contents including a first training object data corresponding to a first activity, extract training scene data from the plurality of training contents including a first training scene data corresponding to the first activity, determine that a probability of the first activity is maximized when the first training object data and the first training scene data both exist in a sample media content.

Background

BACKGROUND(1) Video content has become a part of everyday life with an increasing amount of video content becoming available online, and people spending an increasing amount of time online. Additionally, individuals are able to create and share video content online using video sharing websites and social media. Recognizing visual contents in unconstrained videos has found a new importance in many applications, such as video searches on the Internet, video recommendations, smart advertising, etc. Conventional approaches to content identification rely on manual annotations of video contents, and supervised computer recognition and categorization. However, manual annotations and supervised computer processing are time consuming and expensive.SUMMARY(2) The present disclosure is directed to systems and methods for identifying activities and/or events in media contents based on object data and scene data, substantially as shown in and/or described in connection with at least one of the figures, as set forth more completely in the claims.

Claims

1. A system comprising: a non-transitory memory storing an executable code; and a hardware processor executing the executable code to: receive a plurality of training contents depicting a plurality of activities; extract training object data from the plurality of training contents including a first training object data corresponding to a first activity; extract training scene data from the plurality of training contents including a first training scene data corresponding to the first activity; and determine that a probability of the first activity is maximized when the first training object data and the first training scene data both exist in a sample media content. 10. 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 plurality of training contents depicting a plurality of activities; extracting, using the hardware processor, training object data from the plurality of training contents including a first training object data corresponding to a first activity; extracting, using the hardware processor, training scene data from the plurality of training contents including a first training scene data corresponding to the first activity; and determining, using the hardware processor, a probability is maximized that the first activity is shown when the first training object data and the first training scene data are both included in a sample media content. 20. A system for determining whether a media content includes a first activity using an activity database, the activity database including activity object data and activity scene data for a plurality of activities including the first activity, the system comprising: a non-transitory memory storing an activity identification software; a hardware processor executing the activity identification software to: receive a first media content including a first object data and a first scene data; compare the first object data and the first scene data with the activity object data and the activity scene data of the activity database, respectively; and determine that the first media content probably includes the first activity when the comparing finds a match for both the first object data and the first scene data in the activity database.