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Content based image retrieval with LIRe
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Content based image retrieval with LIRe

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  • 1. CBIR with LIReMathias LuxKlagenfurt UniversityAustria 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

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