Method of and system for generating metadata
US-2016335500-A1 · Nov 17, 2016 · US
US9443147B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9443147-B2 |
| Application number | US-76711410-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 26, 2010 |
| Priority date | Apr 26, 2010 |
| Publication date | Sep 13, 2016 |
| Grant date | Sep 13, 2016 |
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Many internet users consume content through online videos. For example, users may view movies, television shows, music videos, and/or homemade videos. It may be advantageous to provide additional information to users consuming the online videos. Unfortunately, many current techniques may be unable to provide additional information relevant to the online videos from outside sources. Accordingly, one or more systems and/or techniques for determining a set of additional information relevant to an online video are disclosed herein. In particular, visual, textual, audio, and/or other features may be extracted from an online video (e.g., original content of the online video and/or embedded advertisements). Using the extracted features, additional information (e.g., images, advertisements, etc.) may be determined based upon matching the extracted features with content of a database. The additional information may be presented to a user consuming the online video.
Opening claim text (preview).
What is claimed is: 1. A method of identifying digital content relevant to an online video, comprising: identifying, by one or more processing units, promotional content embedded within the online video, the promotional content being generated by a first content producer; extracting, by the one or more processing units, a feature from the promotional content embedded in the online video, the feature comprising at least one of a textual feature, a visual feature, or an audio feature; searching, by the one or more processing units, a database to identify additional information based upon the feature, the additional information being generated by a second content producer different than the first content producer; identifying, by the one or more processing units, candidates from the additional information, the candidates including at least two of a textual feature, a visual feature, or an audio feature; aggregating, by the one or more processing units, the candidates into an aggregate video; and outputting, by the one or more processing units, the aggregate video for presentation. 2. The method of claim 1 , wherein outputting the aggregate video for presentation comprises: presenting the aggregate video and the promotional content sequentially. 3. The method of claim 1 , the visual feature comprising a color histogram. 4. The method of claim 1 , the extracting the feature comprising at least one of: extracting the textual feature using an OCR text recognition technique; or extracting the visual feature using a scale-invariant feature transformation. 5. The method of claim 1 , the searching the database to identify the additional information comprising: executing a multi modal relevance matching algorithm against the database using the feature to determine the additional information. 6. The method of claim 1 , the aggregate video being formatted to be embedded in the online video. 7. The method of claim 1 , the extracting the feature comprising: parsing the promotional content embedded in the online video into one or more segments, each of the one or more segments comprising a sequence of frames; for respective segments, extracting one or more keyframes; and extracting the feature from the one or more keyframes of respective segments. 8. The method of claim 7 , the extracting one or more keyframes comprising at least one of: selecting a middle frame as a keyframe; or selecting a frame having a video quality above a threshold as the keyframe. 9. The method of claim 1 , wherein the aggregate video comprises advertising information associated with the promotional content embedded within the online video. 10. A system for identifying digital content relevant to an online video, comprising: one or more processing units; and a memory storing: a parsing component configured to, when executed by the one or more processing units: select a frame of an online video as a keyframe based upon the frame having a video quality above a threshold; a feature extraction component configured to, when executed by the one or more processing units: identify promotional content embedded within the keyframe, the promotional content being generated by a first content producer; and extract a feature from at least the promotional content embedded within the keyframe, the feature comprising at least one of a textual feature, a visual feature, or an audio feature; an information extraction component configured to, when executed by the one or more processing units: search a database to identify additional information based upon the feature, the additional information being generated by a second content provider different than the first content producer; identify candidates from the additional information determined to be associated with the feature extracted from the promotional content, the candidates including at least two of a textual feature, a visual feature, or an audio feature; and in response to identifying the candidates, automatically aggregate the candidates into an aggregate video; and a presentation component configured to, when executed by the one or more processing units: present the aggregate video. 11. The system of claim 10 , the presentation component further configured to: present the online video sequentially with the aggregate video. 12. The system of claim 11 , the aggregate video being different than the promotional content. 13. The system of claim 10 , the parsing component further configured to: parse the online video into one or more segments, a segment comprising a sequence of frames; and for respective segments, extract one or more keyframes. 14. The system of claim 10 , the information extraction component further configured to: execute a multi modal relevance matching algorithm against the database using the feature to determine the additional information. 15. The system of claim 14 , the multimodal relevance matching algorithm further configured to: perform a text based search algorithm upon the database using the textual feature to determine a first list of candidate additional information; perform a visual feature matching algorithm upon the database using the visual feature to determine a second list of candidate additional information; and perform a linear combination of the first list and second list to generate a set of additional information. 16. A computer-readable storage device comprising processor-executable instructions that, when executed, cause a computing device to perform a method for identifying digital content relevant to an online video, the method comprising: selecting a frame of the online video as a keyframe based upon the frame having a video quality above a threshold; identifying promotional content embedded within the keyframe, the promotional content being generated by a first content producer; extracting a feature from at least the promotional content embedded in the keyframe, the feature comprising at least one of a textual feature, a visual feature, or an audio feature; searching a database to identify additional information based upon the feature, the additional information being generated by a second content producer different than the first content producer; identifying candidates from the additional information determined to be associated with the feature extracted from the promotional content, the candidates including at least two of a texture feature, a visual feature, or an audio feature; in response to identifying the candidates, automatically aggregating the candidates into an aggregate video; and outputting the aggregate video for presentation. 17. The computer-readable storage device of claim 16 , the method comprising: presenting the online video sequentially with the aggregate video.
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