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Computer Vision Group Department of Computer Science University of Illinois at Urbana-Champaign
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Multimodal Information Access & Synthesis Sang Hyun Park Joel Quintana Robert Rand David Forsyth Recognition and Efficient Retrieval of Similar Images in Large Datasets Using Visual Words
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Multimodal Information Access & Synthesis Abstract Process Demo Results Future Work Questions Outline
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Multimodal Information Access & Synthesis Problem: We want to... Identify pictures by content rather than color. Compare large sets of images to find near duplicates. Recognize similar pictures despite small changes. Challenges: Similar Images can be... in different filenames. in different formats. in different sizes and arrangements. stretched, skewed, colored and otherwise altered. Abstract
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Multimodal Information Access & Synthesis Why would we want to find near duplicate images? News Reports Forged Photos Social Networks Picture/Mugshot Matching Weapon & Symbol ID Application
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Multimodal Information Access & Synthesis Process Images Database Part1: Get the Visual Words Extract SIFT Features Interest Points Database Group Similar Interest Points (Kmeans) List of General Points (Visual Words)
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Multimodal Information Access & Synthesis Process Original Images Database Part2: Store Histograms of Visual Words of the Images on the Database Image Add Histogram to the Histograms Database Histograms Database Calculate Histogram of Visual Words Histogram of Visual Words
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Multimodal Information Access & Synthesis Process Part3: Retrieval of Similar Images New Image Histograms Database Calculate Histogram of Visual Words Histogram of Visual Words Query For Nearest Neighbors List Of Nearest Neighbors
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Multimodal Information Access & Synthesis Demo
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Current Configuration –10 Interest points per image –3000 Visual words (K-mean Clustering) –KDTree to get approximate nearest neighbors –Precision : ~0.50 Future Configuration –All Interest points from images –More Clustering Algorithms (Hierarchical K-means / KDTree) –Usage of Full Potential of FLANN Results
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Multimodal Information Access & Synthesis Bigger Database – Web (Image Search Engine / Flicker / Facebook) Multiple Queries –Parallelized Processing (Efficient Processing of Queries) Other Application –Detection of objects inside images: logos, symbols, tattoos, weapons, etc –Finding relationships between people according to their common pictures on social networks Future Work
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Multimodal Information Access & Synthesis Questions
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