Systems, methods, and devices for determining an introduction portion in a video program

Patent metadata

Field	Value
Publication number	US-11615622-B2
Application number	US-202016929250-A
Country	US
Kind code	B2
Filing date	Jul 15, 2020
Priority date	Jul 15, 2020
Publication date	Mar 28, 2023
Grant date	Mar 28, 2023

Abstract

Systems, methods, and devices relating to determining an introduction portion in a video program are described herein. A method may determine first and second hard-matching pairs of video segments in first and second video content such that video fingerprints of the first hard-matching pair match and video fingerprints of the second hard-matching pair also match. The method may classify a third pair of video segments in the first and second video content, sequentially between the first and second hard-matching pairs, as a soft-matching pair of video segments of an introduction portion. The method may use the classification of the third pair of video segments as a soft-matching pair to determine a model configured to determine that a pair of video segments in two video content items are a soft-matching pair of video segments of an introduction portion.

First claim

What is claimed is:

1. A method comprising:
receiving first video content comprising video segments and second video content comprising video segments, wherein the second video content is associated with the first video content;
determining a first hard-matching pair of video segments of the first video content and the second video content, wherein video fingerprints of the first hard-matching pair of video segments match;
determining a second hard-matching pair of video segments in the first video content and the second video content, wherein video fingerprints of the second hard-matching pair of video segments match;
classifying a third pair of video segments in the first video content and the second video content as a soft-matching pair of video segments of an introduction portion of at least one of the first video content or the second video content, wherein the third pair of video segments is sequentially between the first hard-matching pair of video segments and the second hard-matching pair of video segments, wherein video fingerprints of the third pair of video segments do not match; and
determining, based on the classifying the third pair of video segments as a soft-matching pair of video segments of an introduction portion of at least one of the first video content or the second video content, a model configured to determine that a pair of video segments in two video content items are a soft-matching pair of video segments of an introduction portion of at least one of the two video content items.

2. The method of claim 1 , wherein the first video content comprises at least a portion of a first episode of a video program series and the second video content comprises at least a portion of a second episode of the video program series.

3. The method of claim 1 , wherein the first video content comprises target video content in which the introduction portion is not known and the second video content comprises reference video content in which the introduction portion is known.

4. The method of claim 1 , further comprising:
determining the model via machine learning, wherein a training data input for the machine learning comprises the video fingerprints of the third pair of video segments, and a training data output for the machine learning comprises the classification of the third pair of video segments as a soft-matching pair of video segments of an introduction portion of at least one of the first video content or the second video content.

5. The method of claim 4 , wherein the model comprises a regressor model and a training data input for determining the regressor model comprises a difference between the video fingerprints of the third pair of video segments.

6. The method of claim 1 , wherein:
a difference between lengths of the first hard-matching pair of video segments satisfies a length threshold, and
a difference between lengths of the second hard-matching pair of video segments satisfies the length threshold.

7. The method of claim 6 , wherein a difference between lengths of the third pair of video segments does not satisfy the length threshold.

8. The method of claim 1 , wherein the video segments of the first video content comprise respective shots in the first video content and the video segments of the second video content comprise respective shots in the second video content.

9. The method of claim 1 , wherein a video fingerprint of a video segment comprises an alphanumeric value, and a matching pair of video fingerprints each comprise the same alphanumeric value.

10. A method comprising:
determining one or more soft-matching pairs of video segments among a plurality of video content items, wherein each of the one or more soft-matching pairs of video segments comprises a first video segment of one of the plurality of video content items and a second video segment of a different one of the plurality of video content items, wherein a characteristic of the first and second video segments of each soft-matching pair does not match, and wherein each of the one or more soft matching pairs of video segments is located within the corresponding video content items between two hard- matching pairs of video segments of the video content items; and
determining, based on the determining the one or more soft-matching pairs of video segments, a model configured to determine that a pair of video segments comprises common video content.

11. The method of claim 10 , wherein the plurality of video contents items comprises different episodes of one or more video programs.

12. The method of claim 11 , wherein the first video segment and the second video segment of each soft-matching pair are associated with two episodes of a same video program.

13. The method of claim 10 , wherein the first characteristic comprises audio elements, an audio fingerprint, closed captioning data, subtitle data, on-screen text, or a detected visual feature.

14. The method of claim 10 , wherein common video content comprises at least one of an introduction portion, a closing portion, or an advertisement.

15. A device comprising:
one or more processors; and
memory storing instructions that, when executed by the one or more processors cause the device to:
receive first video content comprising video segments and second video content comprising video segments, wherein the second video content is associated with the first video content;
determine a first hard-matching pair of video segments of the first video content and the second video content, wherein video fingerprints of the first hard-matching pair of video segments match;
determine a second hard-matching pair of video segments in the first video content and the second video content, wherein video fingerprints of the second hard-matching pair of video segments match;
classify a third pair of video segments in the first video content and the second video content as a soft-matching pair of video segments of an introduction portion of at least one of the first video content or the second video content, wherein the third pair of video segments is sequentially between the first hard-matching pair of video segments and the second hard-matching pair of video segments, wherein video fingerprints of the third pair of video segments do not match; and
determine, based on the classifying the third pair of video segments as a soft-matching pair of video segments of an introduction portion of at least one of the first video content or the second video content, a model configured to determine that a pair of video segments in two video content items are a soft-matching pair of video segments of an introduction portion of at least one of the two video content items.

16. The device of claim 15 , wherein the first video content comprises at least a portion of a first episode of a video program series and the second video content comprises at least a portion of a second episode of the video program series.

17. The device of claim 15 , wherein the first video content comprises target video content in which the introduction portion is not known and the second video content comprises reference video content in which the introduction portion is known.

18. The device of claim 15 , wherein the instructions, when executed by the one or more processors, further cause the device to:
determine the model via machine learning, wherein a training data input for the machine learning comprises the video fingerprints of the third pair of video segments, and a training data output for the machine learning comprises the classification of the third pair of v

Assignees

• Comcast Cable Comm Llc

Inventors

• Younessian Ehsan
• Ishtiaq Faisal
• Braskich Anthony
• Spier Benjamin

Classifications

• H04N21/47217

  for controlling playback functions for recorded or on-demand content, e.g. using progress bars, mode or play-point indicators or bookmarks (specific graphical features in visual interfaces H04N21/4312) · CPC title

• G06V20/41 Primary

  Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items (segmenting video sequences G06V20/49) · CPC title

• H04N21/8456

  by decomposing the content in the time domain, e.g. in time segments · CPC title

• G06V20/48 Primary

  Matching video sequences · CPC title

• H04N21/4394

  involving operations for analysing the audio stream, e.g. detecting features or characteristics in audio streams (arrangements characterised by components specially adapted for monitoring, identification or recognition of audio in broadcast systems H04H60/58) · CPC title