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LIRe presentation and poster at ACM MM 2011

Just finished my presentation at ACM MM’s open source competition in 2011. Many interested researchers and developers came by to discuss ideas and developments. I’m looking forward to turning many of those idea into code

For those of you interested in the poster I uploaded it here.

I also uploaded the presentation to slideshare.

Searching with Lire in big datasets

Having received several complaints about the slowness of Lire when searching in 100k+ documents I took my time to write a small how to to explain approaches for search in big (relatively) data sets.

Lire has the ability to create indexes with lots of different features (descriptors, like RGB color histograms or CEDD). While this opens the opportunity to flexibility at search time as we can select the feature at the time we create a query, the index tends to get bigger and bigger and searcher take longer and longer.

With a data set of 121,379 images the index created with the features selected for default in Lire Demo has a size of 14,3 GB on the disk. In contrast to that an index just storing the CEDD feature along with the image identifier has a size of 29 MB.

Due to the size of the index also linear search tends to get slower. While for the index stripped down to the CEDD feature and the identifier searching takes (on a AMD Quad-Core computer with 4GB RAM and Java 1.7) roughly 0.33 seconds, searching the big index takes 7 minutes and 3 seconds.

So if you want to index and search big data sets (> 100.000 images for instance) I recommend to

• select which features you need,
• create the index with a minimum set of features, and
• eventually split the index per feature and select the index on the fly instead of the feature
• also you can load the index into RAM

For more on loading the index to RAM and the option to use local features read on in the developer wiki.

Lire publication in the top 10 downloads of ACM SIGMM

As to be found in this month’s SIGMM record, which is the electronic SIGMM newsletter, a publication about Lire is in the top 10 downloads of the ACM special interest group on multimedia for September 2011.

I co-authored the paper with Savvas Chatzichristofis:

Mathias Lux, Savvas A. Chatzichristofis. Lire: lucene image retrieval: an extensible java CBIR library. In ACM Multimedia 2008

It’s also the paper I recommend to include in references if Lire is used within a scientific publication, so my thanks also go to the authors citing and therefore pointing to our work!

Lire and Lire Demo v 0.9 released

I just released Lire and Lire Demo in version 0.9 on sourceforge.net. Basically it’s the alpha version with additional speed and stability enhancements for bag of visual words (BoVW) indexing. While this has already been possible in earlier versions I re-furbished vocabulary creation (k-means clustering) and indexing to support up to 4 CPU cores. I also integrated a function to add documents to BoVW indexes incrementally. So a list of major changes since Lire 0.8 includes

• Major speed-up due to change and re-write of indexing strategies for local features
• Auto color correlation and color histogram features improved
• Re-ranking filter based on global features and LSA
• Parallel bag of visual words indexing and search supporting SURF and SIFT including incremental index updates (see also in the wiki)
• Added functionality to Lire Demo including support for new Lire features and a new result list view

Download and try:

• Source and binaries (or as tar.bz2)
• Lire Demo

Lire Demo 0.9 alpha 2 just released

Finally I found some time to go through Lire and fix several of the — for me — most annoying bugs. While this is still work in progress I have a preview with the demo uploaded to sf.net. New features are:

• Auto Color Correlogram and Color Histogram features improved
• Re-ranking based on different features supported
• Enhanced results view
• Much faster indexing (parallel, use -server switch for your JVM)
• Much faster search (re-write of the searhc code in Lire)
• New developer menu for faster switching of search features
• Re-ranking of results based on latent semantic analysis

You can find the updated Lire Demo along with a windows launcher here, Mac and Linux users please run it using “java -jar … ” or double click (if your windows manager supports actions like that

• Download Liredemo v0.9 alpha 2

The source is — of course — GPL and available in the SVN.

Lire 0.7 Released

Lire 0.7 is a major release fixing a lot of bugs and introducing several new features including new descriptor, a simplified way to use descriptors by introducing new generic searchers and indexers as well as an generalized interface for image descriptors. There are also several improvements in indexing and search speed (especially in autocolorcorrelogram). Furthermore retrieval performance was optimized based on the Wang 1000 data set. If you use Lire 0.7 to update an existing version, please make sure that your indices are created newly from scratch. All new features have also found their way into LireDemo, which now also supports multi-threaded indexing.
Thanks for comments, code and general comments go again to Savvas Chatzichristofis, Rodrigo Carvalho Rezende, Marko Keuschnig, Christian Penz, Oge Marques, Anna-Maria Pasterk and Christoph Kofler.

Links:

• Download Lire 0.7 and/or LireDemo 0.7
• Screencast: Introduction to LireDemo

CBIR for Facebook: img(Finder)

Recently Savvas Chatzichristofis released a Facebook app based on his tool img(Rummager) to retrieve the photos of Facebook contacts based on image content. The tool – called img(Finder) – allows to connect to a Facebook account and creates an index based on the CEDD and FCTH image features. img(Finder) indexes the images of all Facebook friends. Querying the index is done by sketch (painting tool is included) or by sample image. Best of all: The tool is open source

Links

• Download and try

Lire accepted for the Open Source Contest @ ACM MM

Although its quite some time ago that I got the acceptance mail I forgot to blog the good news: Lire (Lucene Image Retrieval) has been acccepted to be presented at the ACM Multimedia within the Open Source Contest track. As it is a contest I assume we have chances to win something?

Firefox 3 default page zoom missing …

On my eee PC I really need a browser, which allows zooming the whole page. While using opera a lot I also like Firefox 3 a lot as it runs rather fast and consumes less memory than Firefox 2. However there is one thing, which is really annoying: Firefox 3 does not allow users to set a default zoom level to start with, which is a rather hand feature for my eee PC 701 .

Fortunately a clever developer found the problem and prepared an add-on, which allows default zoom levels and much more: No Squint … thanks go to Jason Tackaberry.

Links:

• No Squint – original home page
• No Squint – at mozilla.org

LIRE v0.6 released: New Image Features

The new release contains three additional features: (i) Tamura texture features, (ii) Color and Edge Directivity Descriptor (CEDD) and (iii) a configurable color histogram implementation. While the last one was integrated for comparison only the other two provide additional improvements, especially the CEDD feature. Furthermore a FastMap implementation was included in the release for optimization of the indexing process in a later release. Also some bugs were fixed in the MPEG-7 EdgeHistogram descriptor provided in the cbir-library jar file and in color-only search. Note that due to the increased number of features the extensive document builder, which extracts all available features, needs significantly more time for extraction than in the last release.

Links:

• Download Lire & LireDemo