1. CBIR with LIRe
Mathias Lux
Klagenfurt University
Austria
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0

2. Lucene Image Retrieval
• Open source
• Java
• Based on Lucene
– text retrieval engine

3. History
• Caliph & Emir
– first release in July 2004
– developed since ~ midth of 2003
• Lire as spin-off product
– first release in 2006
– first use case was
„barrique“
– Just MPEG-7
Barrique is a project of Roman Kern: http://sourceforge.net/projects/barrique/

4. Image Retrieval Features
• Color Histograms
• MPEG-7 features
– scalable color, color layout and edge histogram
• Tamura features
– coarseness, contrast and directionality
• Joint histograms CEDD, FCTH and JCD
• Auto color correlation
• JPEG coefficients histogram
• Local features
– SIFT , SURF, MSER
• ... and more to come

5. Indexing and Search
• Fast linear search
• BoVW search based on Lucene
• Parallel k-means & visual word indexing
for BoVW
• Fastmap for spatial indexing
• Metric spaces approach for fast search in
global features

6. Lire: Some Examples
• Utilize Lucene
– put an index into RAM
– distribute indexes over the network
• Rapid prototyping
– Basic auto-tagging < 100 loc
• Test different features
& approaches
– eg. mediamid & CEDD

7. Where has LIRe been used?
• ImageCLEF
– different groups
– mentioned on the website
• TRECVid
– 2010 ranked 3rd in known item search
• Medical domain
– image retrieval & video summarization
• Apparel search applications

8. Future Directions …
• Unified way to change & test metrics
• Easier benchmarking
• Further support and maintenance

9. Thanks …
• Want to download & try LIRe:
• http://www.semanticmetadata.net