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  === Pooled Time Series parser for Tika ===
  
- I'm working on integrating Dr. Ryoo's research work into Tika
+ I'm working on [[PooledTimeSeriesParser|integrating Dr. Ryoo's research work 
into Tika]].
- [[http://michaelryoo.com/jpl-interaction.html]]
- [[https://github.com/chrismattmann/pooled_time_series]]
- [[http://arxiv.org/pdf/1412.6505v2.pdf]]
- 
- ==== Metadata Representation ====
- 
- The ultimate goal of the project is to be able to extract metadata from 
videos and index it inside Solr.
- 
- Videos, like images, are just numbers - or a ordered sequence of number - or 
matrices.
- 
- There are many ways in which these numbers can be defined.
- Some popular visual descriptors are Histogram of Gradients, Optical Flow 
vectors, RGB or Color Histograms.
- The challenge is to figure out a way to map this datatype to a datatype that 
can be understood by Solr.
- 
- In the case of color based histograms, we can convert the image into a matrix 
of hex values, where each hex value is the pixel color value
- and index that as a text_ws field in Solr.
- 
- This is what ShutterStock did with respect to an image search tool they've 
built
- 
https://lucidworks.com/blog/shutterstock-searches-35-million-images-color-using-apache-solr/
- 
- Another idea I was thinking of was to index the data as a XHTML document of 
table values,
- 
- where each <tr>..</tr> would be a row of the feature matrix and <td> would be 
the corresponding element in that column.
- 
- However, while performing ranking or querying we would have to compute a 
distance function on these values (for the dataset and the query video)
- 
- How have other users solved this problem? There must be instances of matrix 
type data showing up in other domains, 
- such as geography, physics and other scientific domains. How is the metadata 
designed in such cases?
- 
- 
  
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