Iterative, maximally probable, batch-mode commercial detection for audiovisual content

• US 8,724,967 B2
• Filed: 09/14/2012
• Issued: 05/13/2014
• Est. Priority Date: 11/18/1999
• Status: Active Grant

• Current Assignee: Interval Licensing LLC
• Original Assignee: Interval Licensing LLC
• Inventors: Harville, Michael L.
• Primary Examiner(s): Harvey, David
• Application Number:
  US13/619,789
• Publication Number:
  US 20130014157A1
• Time in Patent Office: 606 Days
• Field of Search: 386249-251
• US Class Current: 386/249
• CPC Class Codes: G11B 27/031 Electronic editing of digitised analogue information signals, e.g. audio or video signals
• CPC Class Codes: H04N 21/438 Interfacing the downstream path of the transmission network originating from a server, e.g. retrieving encoded video stream packets from an IP network
• CPC Class Codes: H04N 21/44008 involving operations for analysing video streams, e.g. detecting features or characteristics in the video stream arrangements characterised by components specially adapted for monitoring, identification or recognition of video in broadcast systems H04H60/59
• CPC Class Codes: H04N 21/812 involving advertisement data advertising per se G06Q30/02
• CPC Class Codes: H04N 5/76 Television signal recording
• CPC Class Codes: H04N 5/781 on disks or drums
• CPC Class Codes: H04N 5/782 on tape
• CPC Class Codes: H04N 5/85 on discs or drums
• CPC Class Codes: H04N 5/907 using static stores, e.g. storage tubes or semiconductor memories H04N5/91 takes precedence
• CPC Class Codes: H04N 7/163 by receiver means only
• CPC Class Codes: H04N 9/87 Regeneration of colour television signals H04N9/80 takes precedence
• CPC Class Codes: Y10S 358/908 Pause control, i.e. "commercial killers"

Abstract

Identification of starting and ending times of commercial breaks and commercials within those commercial breaks found in audiovisual content is disclosed. A solution to a “batch optimization” problem is used in which commercial locations within a set of audiovisual content are detected as a group by choosing a set of commercial locations which optimizes a cost function which can include considerations of, for example, 1) one or more cues, 2) relative locations of commercials within the audiovisual content, and/or 3) probability models based on statistics obtained regarding characteristics of typical commercial and commercial breaks. Optimization can be done over the total set of commercial location decisions, rather than on a per-commercial basis. Additionally, the cost function can be iteratively evaluated and many more types of cues and combinations of cues can be used in detection of commercials.

Claims

1. A non-transitory computer-readable medium storing computer-readable instructions to perform a method for detecting a commercial in a set of audiovisual content spanning a duration of time, the method comprising:

selecting a candidate time within the duration of time spanned by the set of audiovisual content,

wherein the candidate time is identified based on the detection of one or more predetermined cues in a first set of cues, and

wherein the candidate time represents a possible boundary time of a commercial;

assigning a value to the candidate time; and

analyzing the candidate time to determine a likelihood that the candidate time is a commercial boundary time,

wherein the analysis is performed on processing circuitry and includes;

adjusting the value based on one or more cues in a second set of cues occurring within a time interval proximate to the candidate time, and

further adjusting the value based on one or more characteristics of audiovisual content and associated probabilities.

2. The computer-readable medium as in claim 1, wherein the value is further adjusted based, in part, on one or more characteristics of audiovisual content occurring before the candidate time.

3. The computer-readable medium as in claim 1, wherein the value is adjusted based on one or more characteristics of audiovisual content occurring throughout the entire duration of time.

4. A system for detecting a commercial in a set of audiovisual content spanning a duration of time, comprising:

a data storage medium to store the set of audiovisual content; and

a processor coupled to the data storage medium and configured to;

select a candidate time within the duration of time spanned by the set of audiovisual content,

wherein the candidate time is identified based on the detection of one or more predetermined cues in a first set of cues, and

wherein the candidate time represents a possible boundary time of a commercial;

assign a value to the candidate time; and

analyze the candidate time to determine a likelihood that the candidate time is a commercial boundary time,

wherein the analysis is performed on processing circuitry and includes;

adjusting the value based on one or more cues in a second set of cues occurring within a time interval proximate to the candidate time, and

further adjusting the value based on one or more characteristics of audiovisual content and associated probabilities.

5. The system as in claim 4, wherein the value is further adjusted based, in part, on one or more characteristics of audiovisual content occurring before the candidate time.

6. The system as in claim 4, wherein the evaluation is based on one or more characteristics of audiovisual content occurring throughout the entire duration of time.

7. A computer-implemented method for detecting an advertisement in a set of audiovisual content spanning a duration of time, the method comprising:

receiving the set of audiovisual content;

selecting a candidate time identified within the duration of time spanned by the set of audiovisual content,

wherein the candidate time is identified based on the detection of one or more predetermined cues in a first set of cues, and

wherein the candidate time represents a possible boundary time of an advertisement within the audiovisual content;

assigning a value to the candidate time;

analyzing the candidate time to determine a likelihood that the candidate time is an advertisement boundary time, wherein the analysis is performed by processing circuitry; and

adjusting the value of the candidate time based on one or more predetermined cues in a second set of cues,

wherein the second set of cues occur during a time interval proximate to the candidate time.

8. The computer-implemented method of claim 7, wherein the value is further adjusted based, in part, on one or more characteristics of audiovisual content occurring before the candidate time.

9. The computer-implemented method of claim 7, wherein the value is further adjusted based on one or more characteristics of audiovisual content occurring throughout the entire duration of time.