Performer density assessment

Number: 12142042
Published: 2024-11-12
Filed: 2022-05-20
Assignee: Disney Enterprises, Inc.
Inventors: Lucien; Mara Idai et al.
CPC: G06V20/49; G06V20/41; G06V10/70; G06V20/42; G06V20/46
Verdict: Set aside crowd/performer density analytics, business/ops
Source: Google Patents · FreePatentsOnline

Abstract

A system for assessing performer density includes a computing platform having processing hardware and a memory storing software code. The processing hardware is configured to execute the software code to receive content and content data, the content data identifying one or more performer(s) depicted or referenced in the content, and determine, using the content and the content data, one or more segment(s) of the content in which the performer(s) is/are depicted or referenced. The processing hardware is further configured to execute the software code to infer, for each determined segment(s) of the content, a respective importance of the performer(s) in a respective context of each determined segment(s), and calculate, based on the determined segment(s) of the content and the respective importance of the performer(s), a respective density score of each performer with respect to the content.

Background

BACKGROUND (1) Due to its nearly universal popularity as a content medium, ever more audio-video (AV) content is being produced and made available to consumers. As a result, the efficiency with which various creative and commercial aspects of that content can be analyzed and assessed has become increasingly important to a variety of stakeholders, including producers, owners, and distributors of that content, as well as to its investors. (2) One such aspect of interest regarding content is the notion of the overall importance of a particular performer to the storyline and events of the content, which may be a movie or television (TV) episode or series for example. However, a reliable system for assessing performer density within content does not presently exist. Use of acting credits is one current approach to assessing performer density within content, but acting credits tend to be unreliable and inconsistent due to varying approaches to their presentation. For example, some acting credits list characters and the actors who portray them in order of first appearance, while others list the top billed characters or cast first, and still other acting credits list characters and actors in alphabetical order. This makes it difficult for investors, distributors, and audiences to understand the relative importance of different performers within a work. For example, based on acting credits, it is possible to determine whether a favorite or trending actor is in a work, but not whether

Claims

1. A system comprising: a computing platform having a processing hardware and a system memory storing a software code; the processing hardware configured to execute the software code to: receive content and content data, the content data identifying at least one performer depicted or referenced in the content; receive one or more key performance indicators (KPIs) for the content; determine, using the content and the content data, one or more segments of the content in which the at least one performer is depicted or referenced; infer, for each of the determined one or more segments of the content, a respective importance of the at least one performer in a respective context of each of the determined one or more segments of the content; calculate, based on the one or more KPIs, the determined one or more segments of the content and the respective importance of the at least one performer, a respective density score of each of the at least one performer with respect to the content. || 10. A method for use by a system including a computing platform having a processing hardware, and a system memory storing a software code, the method comprising: receiving, by the software code executed by the processing hardware, content and content data, the content data identifying at least one performer depicted or referenced in the content; receiving, by the software code executed by the processing hardware, one or more key performance indicators (KPIs) for the content; determining, by the software code executed by the processing hardware and using the content and the content data, one or more segments of the content in which the at least one performer is depicted or referenced; inferring, by the software code executed by the processing hardware, for each of the determined one or more segments of the content, a respective importance of the at least one performer in a respective context of each of the determined one or more segments of the content; and calculating, by the software code executed by the processing hardware based on the one or more KPIs, the determined one or more segments of the content and the respective importance of the at least one performer, a respective density score of each of the at least one performer with respect to the content.