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https://issues.apache.org/jira/browse/TIKA-2322?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Madhav Sharan updated TIKA-2322:
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Description:
Currently TIKA supports ObjectRecognition in Images. I am proposing to extend
this to support videos.
Idea is -
1. Extract frames from video and run IncV3 to get labels for these frames.
2. We average confidence scores of same labels for each frame.
3. Return results in sorted order of confidence score.
I am writing code for different modes of frame extractions -
1. Extract center image.
2. Extract frames after every fixed interval.
3. Extract N frames equally divided across video.
We used this approach in [0]. Code in [1]
[0] https://github.com/USCDataScience/hadoop-pot
[1] https://github.com/USCDataScience/video-recognition
was:
Currently TIKA supports ObjectRecognition in Images. I am proposing to extend
this to support videos.
Idea is -
1. Extract frames from video and run IncV3 to get labels for these frames.
2. We sum up confidence scores of each frame and label.
3. Return results in sorted order of confidence score.
I am writing code for different modes of frame extractions -
1. Extract center image.
2. Extract frames after every fixed interval.
3. Extract N frames equally divided across video.
We used this approach in [0]. Code in [1]
[0] https://github.com/USCDataScience/hadoop-pot
[1] https://github.com/USCDataScience/video-recognition
> Video labeling using existing ObjectRecognition
> -----------------------------------------------
>
> Key: TIKA-2322
> URL: https://issues.apache.org/jira/browse/TIKA-2322
> Project: Tika
> Issue Type: Improvement
> Components: parser
> Reporter: Madhav Sharan
> Assignee: Chris A. Mattmann
> Labels: memex
> Fix For: 1.15
>
>
> Currently TIKA supports ObjectRecognition in Images. I am proposing to extend
> this to support videos.
> Idea is -
> 1. Extract frames from video and run IncV3 to get labels for these frames.
> 2. We average confidence scores of same labels for each frame.
> 3. Return results in sorted order of confidence score.
> I am writing code for different modes of frame extractions -
> 1. Extract center image.
> 2. Extract frames after every fixed interval.
> 3. Extract N frames equally divided across video.
> We used this approach in [0]. Code in [1]
> [0] https://github.com/USCDataScience/hadoop-pot
> [1] https://github.com/USCDataScience/video-recognition
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